shao
This commit is contained in:
aiolishi
parent
2c8b0beb70
commit
5f65356564
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|
||||
214,45.56249120965429,-73.58319715388312,777.0833333334073,3
|
||||
215,45.518606229301774,-73.59475241426874,1202.9166666666902,20
|
||||
216,45.52203370353778,-73.57113021855815,560.4999999999754,3
|
||||
217,45.52409679671165,-73.57841797764475,790.3333333334133,15
|
||||
218,45.52247779646763,-73.57478446870938,797.5833333334166,20
|
||||
219,45.53961066076051,-73.62661841692122,1156.5000000000657,3
|
||||
220,45.58895991968114,-73.53758992480975,1462.9166666664537,20
|
||||
221,45.54559560319731,-73.5672399814485,1168.0833333333885,1
|
||||
222,45.537473700456566,-73.57729937169172,456.24999999996606,5
|
||||
223,45.57342046906779,-73.6327727768197,1019.7500000001844,0
|
||||
224,45.53557355419221,-73.57917172211978,1167.166666666723,2
|
||||
225,45.50192689559106,-73.62989603799815,478.0833333332944,5
|
||||
226,45.55114485440528,-73.53770269990456,1599.7499999996626,3
|
||||
227,45.53782697365083,-73.61519170037559,1578.0833333330156,5
|
||||
228,45.52940323053624,-73.58716197505838,494.49999999995737,18
|
||||
229,45.55301895367002,-73.58388794985183,1705.1666666662334,8
|
||||
230,45.55058908283418,-73.57424335824136,947.6666666668182,1
|
||||
231,45.49619083697144,-73.62436735080055,114.49999999999784,13
|
||||
232,45.5389132118943,-73.5792013969,759.4166666667326,2
|
||||
233,45.535798184139765,-73.58664104188827,1567.6666666663584,2
|
||||
234,45.5313114537718,-73.58372215024325,547.9999999999698,3
|
||||
235,45.52036705536745,-73.59761235604635,978.3333333334988,0
|
||||
236,45.48313978581276,-73.57653648384526,673.08333333336,23
|
||||
237,45.55297824741078,-73.59484359129024,1354.666666666552,5
|
||||
238,45.55430120710761,-73.56162491267922,1355.1666666665517,2
|
||||
239,45.57092278674684,-73.57715490720366,898.0000000001289,10
|
||||
240,45.53361097030694,-73.60106645724453,701.6666666667063,11
|
||||
241,45.52227967073674,-73.5684337774366,873.1666666667843,21
|
||||
242,45.57044282123756,-73.52518192920604,235.41666666667595,7
|
||||
243,45.48626024282493,-73.63860168141315,998.6666666668414,18
|
||||
244,45.54717058947268,-73.55625786283633,951.41666666682,3
|
||||
245,45.546481863801525,-73.5749389146122,795.4166666667489,2
|
||||
246,45.495523127814025,-73.62772501663683,425.749999999973,8
|
||||
247,45.52119924708915,-73.581789228748,1044.8333333335006,17
|
||||
248,45.53256430507208,-73.5675347056023,694.9166666667032,5
|
||||
|
|
|
@ -0,0 +1,237 @@
|
|||
Plotly Express 是一个新的高级 Python 可视化库，它是 Plotly.py 的高级封装，为复杂图表提供简单的语法。最主要的是 Plotly 可以与 Pandas 数据类型 DataFrame 完美的结合，对于数据分析、可视化来说实在是太便捷了，而且是完全免费的，非常值得尝试
|
||||
|
||||
下面我们使用 Ployly 的几个内置数据集来进行相关图表绘制的演示
|
||||
|
||||
数据集
|
||||
|
||||
Plotly 内置的所有数据集都是 DataFrame 格式，也即是与 Pandas 深度契合的体现
|
||||
|
||||
不同国家历年GDP收入与人均寿命
|
||||
|
||||
包含字段：国家、洲、年份、平均寿命、人口数量、GDP、国家简称、国家编号
|
||||
|
||||
gap = px.data.gapminder()gap2007 = gap.query("year==2007")gap2007
|
||||
|
||||
Output
|
||||
|
||||
餐馆的订单流水
|
||||
|
||||
包含字段：总账单、小费、性别、是否抽烟、星期几、就餐时间、人数
|
||||
|
||||
tips = px.data.tips()tips
|
||||
|
||||
Output
|
||||
|
||||
鸢尾花
|
||||
|
||||
包含字段：萼片长、萼片宽、花瓣长、花瓣宽、种类、种类编号
|
||||
|
||||
iris = px.data.iris() iris
|
||||
|
||||
Output
|
||||
|
||||
风力数据
|
||||
|
||||
包含字段：方向、强度、数值
|
||||
|
||||
wind = px.data.wind() wind
|
||||
|
||||
Output
|
||||
|
||||
2013年蒙特利尔市长选举投票结果
|
||||
|
||||
包括字段：区域、Coderre票数、Bergeron票数、Joly票数、总票数、胜者、结果(占比分类)
|
||||
|
||||
election = px.data.election() election
|
||||
|
||||
Output
|
||||
|
||||
蒙特利尔一个区域中心附近的汽车共享服务的可用性
|
||||
|
||||
包括字段：纬度、经度、汽车小时数、高峰小时
|
||||
|
||||
carshare = px.data.carshare()carshare
|
||||
|
||||
Output
|
||||
|
||||
内置调色板
|
||||
|
||||
Plotly 还拥有众多色彩高级的调色板，使得我们在绘制图表的时候不再为颜色搭配而烦恼
|
||||
|
||||
卡通片的色彩和序列
|
||||
|
||||
px.colors.carto.swatches()
|
||||
|
||||
Output
|
||||
|
||||
CMOcean项目的色阶
|
||||
|
||||
px.colors.cmocean.swatches()
|
||||
|
||||
Output
|
||||
|
||||
还有其他很多调色板供选择，就不一一展示了，下面只给出代码，具体颜色样式可以自行运行代码查看
|
||||
|
||||
ColorBrewer2项目的色阶
|
||||
|
||||
px.colors.colorbrewer
|
||||
|
||||
周期性色标，适用于具有自然周期结构的连续数据
|
||||
|
||||
px.colors.cyclical
|
||||
|
||||
分散色标，适用于具有自然终点的连续数据
|
||||
|
||||
px.colors.diverging
|
||||
|
||||
定性色标，适用于没有自然顺序的数据
|
||||
|
||||
px.colors.qualitative
|
||||
|
||||
顺序色标，适用于大多数连续数据
|
||||
|
||||
px.colors.sequential
|
||||
|
||||
Plotly Express 基本绘图
|
||||
|
||||
散点图
|
||||
|
||||
Plotly 绘制散点图非常容易，一行代码就可以完成
|
||||
|
||||
px.scatter(gap2007, x="gdpPercap", y="lifeExp")
|
||||
|
||||
Output
|
||||
|
||||
还可以通过参数 color 来区分不同的数据类别
|
||||
|
||||
px.scatter(gap2007, x="gdpPercap", y="lifeExp", color="continent")
|
||||
|
||||
Output
|
||||
|
||||
这里每个点都代表一个国家，不同颜色则代表不同的大洲
|
||||
|
||||
可以使用参数 size 来体现数据的大小情况
|
||||
|
||||
px.scatter(gap2007, x="gdpPercap", y="lifeExp", color="continent", size="pop", size_max=60)
|
||||
|
||||
Output
|
||||
|
||||
还可以通过参数 hover_name 来指定当鼠标悬浮的时候，展示的信息
|
||||
|
||||
还可以根据数据集中不同的数据类型进行图表的拆分
|
||||
|
||||
px.scatter(gap2007, x="gdpPercap", y="lifeExp", color="continent", size="pop", size_max=60, hover_name="country", facet_col="continent", log_x=True)
|
||||
|
||||
Output
|
||||
|
||||
我们当然还可以查看不同年份的数据，生成自动切换的动态图表
|
||||
|
||||
px.scatter(gap, x="gdpPercap", y="lifeExp", color="continent", size="pop", size_max=60, hover_name="country", animation_frame="year", animation_group="country", log_x=True, range_x=[100, 100000], range_y=[25, 90], labels=dict(pop="Population", gdpPercap="GDP per Capa", lifeExp="Life Expectancy"))
|
||||
|
||||
Output
|
||||
|
||||
地理信息图
|
||||
|
||||
Plotly 绘制动态的地理信息图表也是非常方便，通过这种地图的形式，我们也可以清楚的看到数据集中缺少前苏联的相关数据
|
||||
|
||||
px.choropleth(gap, locations="iso_alpha", color="lifeExp", hover_name="country", animation_frame="year", color_continuous_scale=px.colors.sequential.Plasma, projection="natural earth")
|
||||
|
||||
Output
|
||||
|
||||
矩阵散点图
|
||||
|
||||
px.scatter_matrix(iris, dimensions=['sepal_width', 'sepal_length', 'petal_width', 'petal_length'], color='species', symbol='species')
|
||||
|
||||
Output
|
||||
|
||||
平行坐标图
|
||||
|
||||
px.parallel_coordinates(tips, color='size', color_continuous_scale=px.colors.sequential.Inferno)
|
||||
|
||||
Output
|
||||
|
||||
三元散点图
|
||||
|
||||
px.scatter_ternary(election, a="Joly", b="Coderre", c="Bergeron", color="winner", size="total", hover_name="district", size_max=15, color_discrete_map = {"Joly": "blue", "Bergeron": "green", "Coderre":"red"} )
|
||||
|
||||
Output
|
||||
|
||||
极坐标线条图
|
||||
|
||||
px.line_polar(wind, r="frequency", theta="direction", color="strength", line_close=True,color_discrete_sequence=px.colors.sequential.Plotly3[-2::-1])
|
||||
|
||||
Output
|
||||
|
||||
小提琴图
|
||||
|
||||
px.violin(tips, y="tip", x="sex", color="smoker", facet_col="day", facet_row="time",box=True, points="all", category_orders={"day": ["Thur", "Fri", "Sat", "Sun"], "time": ["Lunch", "Dinner"]}, hover_data=tips.columns)
|
||||
|
||||
Output
|
||||
|
||||
极坐标条形图
|
||||
|
||||
px.bar_polar(wind, r="frequency", theta="direction", color="strength", color_discrete_sequence= px.colors.sequential.Plotly3[-2::-1])
|
||||
|
||||
Output
|
||||
|
||||
并行类别图
|
||||
|
||||
px.parallel_categories(tips, color="size", color_continuous_scale=px. colors.sequential.Inferno)
|
||||
|
||||
Output
|
||||
|
||||
直方图
|
||||
|
||||
px.histogram(tips, x="total_bill", color="smoker",facet_row="day", facet_col="time")
|
||||
|
||||
Output
|
||||
|
||||
三维散点图
|
||||
|
||||
px.scatter_3d(election, x="Joly", y="Coderre", z="Bergeron", color="winner", size="total", hover_name="district",symbol="result", color_discrete_map = {"Joly": "blue", "Bergeron": "green", "Coderre":"red"})
|
||||
|
||||
Output
|
||||
|
||||
密度等值线图
|
||||
|
||||
px.density_contour(iris, x="sepal_width", y="sepal_length", color="species")
|
||||
|
||||
Output
|
||||
|
||||
箱形图
|
||||
|
||||
px.box(tips, x="sex", y="tip", color="smoker", notched=True)
|
||||
|
||||
Output
|
||||
|
||||
地理坐标线条图
|
||||
|
||||
px.line_geo(gap.query("year==2007"), locations="iso_alpha", color="continent", projection="orthographic")
|
||||
|
||||
Output
|
||||
|
||||
条线图
|
||||
|
||||
px.line(gap, x="year", y="lifeExp", color="continent", line_group="country", hover_name="country", line_shape="spline", render_mode="svg")
|
||||
|
||||
Output
|
||||
|
||||
面积图
|
||||
|
||||
px.area(gap, x="year", y="pop", color="continent", line_group="country")
|
||||
|
||||
Output
|
||||
|
||||
热力图
|
||||
|
||||
px.density_heatmap(iris, x="sepal_width", y="sepal_length", marginal_x="rug", marginal_y="histogram")
|
||||
|
||||
Output
|
||||
|
||||
条形图
|
||||
|
||||
px.bar(tips, x="sex", y="total_bill", color="smoker", barmode="group")
|
||||
|
||||
Output
|
||||
|
||||
总体来说，Plotly/Plotly Express 还是非常强大绘图工具，值得我们细细研究
|
||||
|
|
@ -0,0 +1,59 @@
|
|||
,district,Coderre,Bergeron,Joly,total,winner,result,district_id
|
||||
0,101-Bois-de-Liesse,2481,1829,3024,7334,Joly,plurality,101
|
||||
1,102-Cap-Saint-Jacques,2525,1163,2675,6363,Joly,plurality,102
|
||||
2,11-Sault-au-Récollet,3348,2770,2532,8650,Coderre,plurality,11
|
||||
3,111-Mile-End,1734,4782,2514,9030,Bergeron,majority,111
|
||||
4,112-DeLorimier,1770,5933,3044,10747,Bergeron,majority,112
|
||||
5,113-Jeanne-Mance,1455,3599,2316,7370,Bergeron,plurality,113
|
||||
6,12-Saint-Sulpice,3252,2521,2543,8316,Coderre,plurality,12
|
||||
7,121-La Pointe-aux-Prairies,5456,1760,3330,10546,Coderre,majority,121
|
||||
8,122-Pointe-aux-Trembles,4734,1879,2852,9465,Coderre,majority,122
|
||||
9,123-Rivière-des-Prairies,5737,958,1656,8351,Coderre,majority,123
|
||||
10,13-Ahuntsic,2979,3430,2873,9282,Bergeron,plurality,13
|
||||
11,131-Saint-Édouard,1827,6408,2815,11050,Bergeron,majority,131
|
||||
12,132-Étienne-Desmarteau,2331,5748,2788,10867,Bergeron,majority,132
|
||||
13,133-Vieux-Rosemont,2670,4962,3234,10866,Bergeron,plurality,133
|
||||
14,134-Marie-Victorin,3673,3155,2431,9259,Coderre,plurality,134
|
||||
15,14-Bordeaux-Cartierville,3612,1554,2081,7247,Coderre,plurality,14
|
||||
16,141-Côte-de-Liesse,4308,1320,3959,9587,Coderre,plurality,141
|
||||
17,142-Norman-McLaren,4104,1459,2822,8385,Coderre,plurality,142
|
||||
18,151-Saint-Léonard-Est,3931,882,1641,6454,Coderre,majority,151
|
||||
19,152-Saint-Léonard-Ouest,5387,1184,1908,8479,Coderre,majority,152
|
||||
20,161-Saint-HenriPetite-BourgognePointe-Saint-Charles,2432,3368,3578,9378,Joly,plurality,161
|
||||
21,162-Saint-PaulÉmard,2566,2092,2438,7096,Coderre,plurality,162
|
||||
22,171-ChamplainL'Île-des-Soeurs,3347,2562,3291,9200,Coderre,plurality,171
|
||||
23,172-Desmarchais-Crawford,2476,2631,2849,7956,Joly,plurality,172
|
||||
24,181-Peter-McGill,1451,754,1894,4099,Joly,plurality,181
|
||||
25,182-Saint-Jacques,1906,2169,2282,6357,Joly,plurality,182
|
||||
26,183-Sainte-Marie,1347,2827,2271,6445,Bergeron,plurality,183
|
||||
27,191-Saint-Michel,3668,984,1220,5872,Coderre,majority,191
|
||||
28,192-François-Perrault,2878,2666,2039,7583,Coderre,plurality,192
|
||||
29,193-Villeray,2201,5819,2782,10802,Bergeron,majority,193
|
||||
30,194-Parc-Extension,2420,1793,1402,5615,Coderre,plurality,194
|
||||
31,21-Ouest,2184,691,1076,3951,Coderre,majority,21
|
||||
32,22-Est,1589,708,1172,3469,Coderre,plurality,22
|
||||
33,23-Centre,2526,851,1286,4663,Coderre,majority,23
|
||||
34,31-Darlington,1873,1182,1232,4287,Coderre,plurality,31
|
||||
35,32-Côte-des-Neiges,1644,1950,1578,5172,Bergeron,plurality,32
|
||||
36,33-Snowdon,1548,1503,1636,4687,Joly,plurality,33
|
||||
37,34-Notre-Dame-de-Grâce,1773,2653,3262,7688,Joly,plurality,34
|
||||
38,35-Loyola,2040,1437,2648,6125,Joly,plurality,35
|
||||
39,41-du Canal,1165,832,1266,3263,Joly,plurality,41
|
||||
40,42-J.-Émery-Provost,1193,653,1157,3003,Coderre,plurality,42
|
||||
41,43-Fort-Rolland,1325,1205,1908,4438,Joly,plurality,43
|
||||
42,51-Sault-Saint-Louis,4201,1642,3717,9560,Coderre,plurality,51
|
||||
43,52-Cecil-P.-Newman,3536,1330,2943,7809,Coderre,plurality,52
|
||||
44,61-Pierre-Foretier,631,258,998,1887,Joly,majority,61
|
||||
45,62-Denis-Benjamin-Viger,595,226,1068,1889,Joly,majority,62
|
||||
46,63-Jacques-Bizard,518,224,690,1432,Joly,plurality,63
|
||||
47,64-Sainte-Geneviève,332,131,326,789,Coderre,plurality,64
|
||||
48,71-Tétreaultville,3694,2589,3454,9737,Coderre,plurality,71
|
||||
49,72-MaisonneuveLongue-Pointe,2746,3250,3139,9135,Bergeron,plurality,72
|
||||
50,73-Hochelaga,1546,3679,2675,7900,Bergeron,plurality,73
|
||||
51,74-Louis-Riel,3509,2178,2338,8025,Coderre,plurality,74
|
||||
52,81-Marie-Clarac,6591,1085,1435,9111,Coderre,majority,81
|
||||
53,82-Ovide-Clermont,6229,780,1051,8060,Coderre,majority,82
|
||||
54,91-Claude-Ryan,996,643,423,2062,Coderre,plurality,91
|
||||
55,92-Joseph-Beaubien,540,833,592,1965,Bergeron,plurality,92
|
||||
56,93-Robert-Bourassa,446,465,419,1330,Bergeron,plurality,93
|
||||
57,94-Jeanne-Sauvé,491,698,489,1678,Bergeron,plurality,94
|
||||
|
|
|
@ -0,0 +1,101 @@
|
|||
,experiment_1,experiment_2,experiment_3,gender,group
|
||||
0,96.87606524104424,93.41794186205836,73.03319261806172,male,control
|
||||
1,87.30133583529452,129.60339543098098,66.05655384860344,female,control
|
||||
2,97.69131206443264,106.18791583747864,103.42270945298878,male,treatment
|
||||
3,102.97815237236064,93.8146817305033,56.99587018931086,female,treatment
|
||||
4,87.10699272862477,107.01998547962673,72.14029211350231,male,control
|
||||
5,106.650988962703,94.01726233779416,76.62440110809008,female,control
|
||||
6,101.96789610675285,95.08891880671696,111.81685216636848,male,treatment
|
||||
7,117.78402141130046,115.39140402812605,98.64938286937958,female,treatment
|
||||
8,115.41235439928084,105.13793762581705,96.28039576038483,male,control
|
||||
9,107.3273448045416,134.4989267139621,86.43129372481046,female,control
|
||||
10,99.6172541280035,106.19263647197582,97.9614052031477,male,treatment
|
||||
11,100.90801801849013,98.49773453074349,81.57649628140524,female,treatment
|
||||
12,103.73322930003812,103.64300947168036,92.6733901151631,male,control
|
||||
13,96.82862968379752,118.28851360684462,69.04800214309412,female,control
|
||||
14,97.41300576349734,133.81460507676135,85.86631202379608,male,treatment
|
||||
15,111.71546116211962,143.68589169199117,98.9968522988364,female,treatment
|
||||
16,92.99825424103256,119.11313771972604,85.53334112377719,male,control
|
||||
17,103.0370263885008,113.49030757386136,99.17539628161732,female,control
|
||||
18,122.45771222849216,125.57402071454852,110.15293673867568,male,treatment
|
||||
19,111.72093843245534,97.29321087218584,99.82865111091688,female,treatment
|
||||
20,108.59703912851718,114.55578187212689,74.57665002405716,male,control
|
||||
21,86.00067917492646,102.8148302845022,93.4909918341224,female,control
|
||||
22,108.22082997242558,111.2655464432314,96.23192720552623,male,treatment
|
||||
23,107.02254986229214,107.32317041909052,68.64741021134407,female,treatment
|
||||
24,106.68567646477835,125.53691833259457,93.42960247255095,male,control
|
||||
25,98.33722206969595,120.66187625946849,68.27452225629308,female,control
|
||||
26,91.77160903135388,106.11835373702648,84.86622957834284,male,treatment
|
||||
27,114.0102260806097,113.19411909266884,83.2783694811895,female,treatment
|
||||
28,99.36447339671628,128.98211960060868,93.68353539266592,male,control
|
||||
29,102.0848651185468,96.76265139283652,109.4336405768756,female,control
|
||||
30,104.22003927060842,98.53000797317672,84.78250808783284,male,treatment
|
||||
31,90.8419388241776,129.77868819843576,103.4072175445103,female,treatment
|
||||
32,93.0952189075527,117.4908416284272,75.317582722818,male,control
|
||||
33,120.28494035137344,128.10347266036626,115.58696867308667,female,control
|
||||
34,112.79439507221171,108.65787818177574,80.0527938687015,male,treatment
|
||||
35,97.38937970522906,93.97915042860836,106.2872379688312,female,treatment
|
||||
36,105.60548763385378,100.31935141294606,98.61238234207067,male,control
|
||||
37,106.3602628726801,99.20417350710404,70.37381577213912,female,control
|
||||
38,101.58409349079014,106.43997407520592,69.8017451924211,male,treatment
|
||||
39,79.627960848754,126.39982636138508,85.41912263305407,female,treatment
|
||||
40,115.1745293454008,101.21513001268984,43.801175752611606,male,control
|
||||
41,106.53182376731462,107.28672680975174,60.81179285463617,female,control
|
||||
42,94.98263666330396,121.1716702929984,99.41949730696815,male,treatment
|
||||
43,96.78131630120166,127.24938650893672,81.067194207433,female,treatment
|
||||
44,90.53505148745876,106.4738708421859,81.38217435797954,male,control
|
||||
45,97.3724477688896,103.45396742654022,64.5680823183638,female,control
|
||||
46,102.07570100045706,110.42502823706356,82.10664726913008,male,treatment
|
||||
47,113.34644089441548,114.28422515239596,114.0800090383604,female,treatment
|
||||
48,99.16252467399494,115.87027487805348,56.94730371262592,male,control
|
||||
49,115.19093327622592,102.76053814688797,76.81854612272282,female,control
|
||||
50,101.20197149116704,88.65923075825724,84.19773610407385,male,treatment
|
||||
51,102.15438485258844,112.09850718335584,96.88296557581286,female,treatment
|
||||
52,104.84390950771105,92.46744327013312,143.84643208361138,male,control
|
||||
53,88.86870748537869,99.895240748729,95.86144929579538,female,control
|
||||
54,106.99313326342283,94.9336684921247,126.23854648453153,male,treatment
|
||||
55,79.42957481543229,102.10062558140578,105.39919358542934,female,treatment
|
||||
56,79.91007596007512,93.61647573375812,25.528902727455872,male,control
|
||||
57,102.75674518465028,115.6401933040668,85.0183158666797,female,control
|
||||
58,106.50911841835378,109.31644644934065,78.05352942296578,male,treatment
|
||||
59,116.57613978851472,106.18926547435316,89.43052556366084,female,treatment
|
||||
60,105.86488743479735,91.33176428280692,55.15574459592456,male,control
|
||||
61,101.6406509148884,120.14042960264156,103.6598229404085,female,control
|
||||
62,82.45375160201769,119.99866553631976,81.84612840166531,male,treatment
|
||||
63,103.47113336815175,106.97465225615018,99.3315284278933,female,treatment
|
||||
64,111.57539596013696,121.36550691186274,81.13130127077808,male,control
|
||||
65,90.52597523832,98.71650364377432,105.87651496636612,female,control
|
||||
66,125.5204245339222,82.48071301855163,73.5436296499183,male,treatment
|
||||
67,90.21247438443784,90.0325909853458,94.68164053424204,female,treatment
|
||||
68,110.8333387158032,117.96705726440037,112.34804577447116,male,control
|
||||
69,103.86151675950492,110.80555993405694,103.02493792432377,female,control
|
||||
70,83.8308994934392,100.35633403365804,93.73716887483364,male,treatment
|
||||
71,104.89507698266064,103.2406397128152,113.1460990824864,female,treatment
|
||||
72,95.34256875179256,106.71264388984817,89.65914020129773,male,control
|
||||
73,101.3127213745742,112.40253823162678,103.5323883381708,female,control
|
||||
74,88.39280684001895,118.37686641258448,92.9848024432388,male,treatment
|
||||
75,100.51923728271925,89.408981677046,91.39393639000464,female,treatment
|
||||
76,94.49978699806825,112.74449166670784,122.96692500755688,male,control
|
||||
77,115.28544529751144,113.71706929679968,103.10058008500462,female,control
|
||||
78,88.02583256666699,124.43908197971108,92.4851775911426,male,treatment
|
||||
79,108.21594141266117,133.07129566591016,110.2178377106918,female,treatment
|
||||
80,103.97741353721,136.6736157228351,119.81130284877877,male,control
|
||||
81,93.02648850216076,108.40115937104376,87.60512026902201,female,control
|
||||
82,94.75344491514376,137.7421034460475,94.41014090268736,male,treatment
|
||||
83,105.41326143638526,86.92391691963303,91.16612042676972,female,treatment
|
||||
84,89.98571694680537,115.87117118675488,91.76224286416664,male,control
|
||||
85,99.19797691786115,130.11109471859805,83.04163191003826,female,control
|
||||
86,106.45557892554882,100.02567617575396,115.64157104921004,male,treatment
|
||||
87,106.53740176869354,102.49887098636997,89.8283252286509,female,treatment
|
||||
88,100.58494014361828,120.93374474771228,88.39586580661535,male,control
|
||||
89,100.28481061716067,99.53759126542052,116.9537068983502,female,control
|
||||
90,100.17749269798531,104.67370034744938,73.25099641056534,male,treatment
|
||||
91,108.15167224711271,137.99435901344117,105.05479181425382,female,treatment
|
||||
92,101.3205252320304,105.71129083938632,73.73084439286063,male,control
|
||||
93,99.17755784625103,88.57072941909104,78.65504095998203,female,control
|
||||
94,102.77062539939328,129.00227367829714,52.11112167838937,male,treatment
|
||||
95,108.1569641420406,105.97154070236674,64.52402923016913,female,treatment
|
||||
96,91.73999230125186,111.1253771258949,64.26099304241377,male,control
|
||||
97,95.41034685726756,84.44832175269606,75.50599064359672,female,control
|
||||
98,106.36240592567884,115.52238227700173,123.46968854252772,male,treatment
|
||||
99,94.2692372873789,104.6510642690364,92.38748987804956,female,treatment
|
||||
|
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,151 @@
|
|||
,sepal_length,sepal_width,petal_length,petal_width,species,species_id
|
||||
0,5.1,3.5,1.4,0.2,setosa,1
|
||||
1,4.9,3.0,1.4,0.2,setosa,1
|
||||
2,4.7,3.2,1.3,0.2,setosa,1
|
||||
3,4.6,3.1,1.5,0.2,setosa,1
|
||||
4,5.0,3.6,1.4,0.2,setosa,1
|
||||
5,5.4,3.9,1.7,0.4,setosa,1
|
||||
6,4.6,3.4,1.4,0.3,setosa,1
|
||||
7,5.0,3.4,1.5,0.2,setosa,1
|
||||
8,4.4,2.9,1.4,0.2,setosa,1
|
||||
9,4.9,3.1,1.5,0.1,setosa,1
|
||||
10,5.4,3.7,1.5,0.2,setosa,1
|
||||
11,4.8,3.4,1.6,0.2,setosa,1
|
||||
12,4.8,3.0,1.4,0.1,setosa,1
|
||||
13,4.3,3.0,1.1,0.1,setosa,1
|
||||
14,5.8,4.0,1.2,0.2,setosa,1
|
||||
15,5.7,4.4,1.5,0.4,setosa,1
|
||||
16,5.4,3.9,1.3,0.4,setosa,1
|
||||
17,5.1,3.5,1.4,0.3,setosa,1
|
||||
18,5.7,3.8,1.7,0.3,setosa,1
|
||||
19,5.1,3.8,1.5,0.3,setosa,1
|
||||
20,5.4,3.4,1.7,0.2,setosa,1
|
||||
21,5.1,3.7,1.5,0.4,setosa,1
|
||||
22,4.6,3.6,1.0,0.2,setosa,1
|
||||
23,5.1,3.3,1.7,0.5,setosa,1
|
||||
24,4.8,3.4,1.9,0.2,setosa,1
|
||||
25,5.0,3.0,1.6,0.2,setosa,1
|
||||
26,5.0,3.4,1.6,0.4,setosa,1
|
||||
27,5.2,3.5,1.5,0.2,setosa,1
|
||||
28,5.2,3.4,1.4,0.2,setosa,1
|
||||
29,4.7,3.2,1.6,0.2,setosa,1
|
||||
30,4.8,3.1,1.6,0.2,setosa,1
|
||||
31,5.4,3.4,1.5,0.4,setosa,1
|
||||
32,5.2,4.1,1.5,0.1,setosa,1
|
||||
33,5.5,4.2,1.4,0.2,setosa,1
|
||||
34,4.9,3.1,1.5,0.1,setosa,1
|
||||
35,5.0,3.2,1.2,0.2,setosa,1
|
||||
36,5.5,3.5,1.3,0.2,setosa,1
|
||||
37,4.9,3.1,1.5,0.1,setosa,1
|
||||
38,4.4,3.0,1.3,0.2,setosa,1
|
||||
39,5.1,3.4,1.5,0.2,setosa,1
|
||||
40,5.0,3.5,1.3,0.3,setosa,1
|
||||
41,4.5,2.3,1.3,0.3,setosa,1
|
||||
42,4.4,3.2,1.3,0.2,setosa,1
|
||||
43,5.0,3.5,1.6,0.6,setosa,1
|
||||
44,5.1,3.8,1.9,0.4,setosa,1
|
||||
45,4.8,3.0,1.4,0.3,setosa,1
|
||||
46,5.1,3.8,1.6,0.2,setosa,1
|
||||
47,4.6,3.2,1.4,0.2,setosa,1
|
||||
48,5.3,3.7,1.5,0.2,setosa,1
|
||||
49,5.0,3.3,1.4,0.2,setosa,1
|
||||
50,7.0,3.2,4.7,1.4,versicolor,2
|
||||
51,6.4,3.2,4.5,1.5,versicolor,2
|
||||
52,6.9,3.1,4.9,1.5,versicolor,2
|
||||
53,5.5,2.3,4.0,1.3,versicolor,2
|
||||
54,6.5,2.8,4.6,1.5,versicolor,2
|
||||
55,5.7,2.8,4.5,1.3,versicolor,2
|
||||
56,6.3,3.3,4.7,1.6,versicolor,2
|
||||
57,4.9,2.4,3.3,1.0,versicolor,2
|
||||
58,6.6,2.9,4.6,1.3,versicolor,2
|
||||
59,5.2,2.7,3.9,1.4,versicolor,2
|
||||
60,5.0,2.0,3.5,1.0,versicolor,2
|
||||
61,5.9,3.0,4.2,1.5,versicolor,2
|
||||
62,6.0,2.2,4.0,1.0,versicolor,2
|
||||
63,6.1,2.9,4.7,1.4,versicolor,2
|
||||
64,5.6,2.9,3.6,1.3,versicolor,2
|
||||
65,6.7,3.1,4.4,1.4,versicolor,2
|
||||
66,5.6,3.0,4.5,1.5,versicolor,2
|
||||
67,5.8,2.7,4.1,1.0,versicolor,2
|
||||
68,6.2,2.2,4.5,1.5,versicolor,2
|
||||
69,5.6,2.5,3.9,1.1,versicolor,2
|
||||
70,5.9,3.2,4.8,1.8,versicolor,2
|
||||
71,6.1,2.8,4.0,1.3,versicolor,2
|
||||
72,6.3,2.5,4.9,1.5,versicolor,2
|
||||
73,6.1,2.8,4.7,1.2,versicolor,2
|
||||
74,6.4,2.9,4.3,1.3,versicolor,2
|
||||
75,6.6,3.0,4.4,1.4,versicolor,2
|
||||
76,6.8,2.8,4.8,1.4,versicolor,2
|
||||
77,6.7,3.0,5.0,1.7,versicolor,2
|
||||
78,6.0,2.9,4.5,1.5,versicolor,2
|
||||
79,5.7,2.6,3.5,1.0,versicolor,2
|
||||
80,5.5,2.4,3.8,1.1,versicolor,2
|
||||
81,5.5,2.4,3.7,1.0,versicolor,2
|
||||
82,5.8,2.7,3.9,1.2,versicolor,2
|
||||
83,6.0,2.7,5.1,1.6,versicolor,2
|
||||
84,5.4,3.0,4.5,1.5,versicolor,2
|
||||
85,6.0,3.4,4.5,1.6,versicolor,2
|
||||
86,6.7,3.1,4.7,1.5,versicolor,2
|
||||
87,6.3,2.3,4.4,1.3,versicolor,2
|
||||
88,5.6,3.0,4.1,1.3,versicolor,2
|
||||
89,5.5,2.5,4.0,1.3,versicolor,2
|
||||
90,5.5,2.6,4.4,1.2,versicolor,2
|
||||
91,6.1,3.0,4.6,1.4,versicolor,2
|
||||
92,5.8,2.6,4.0,1.2,versicolor,2
|
||||
93,5.0,2.3,3.3,1.0,versicolor,2
|
||||
94,5.6,2.7,4.2,1.3,versicolor,2
|
||||
95,5.7,3.0,4.2,1.2,versicolor,2
|
||||
96,5.7,2.9,4.2,1.3,versicolor,2
|
||||
97,6.2,2.9,4.3,1.3,versicolor,2
|
||||
98,5.1,2.5,3.0,1.1,versicolor,2
|
||||
99,5.7,2.8,4.1,1.3,versicolor,2
|
||||
100,6.3,3.3,6.0,2.5,virginica,3
|
||||
101,5.8,2.7,5.1,1.9,virginica,3
|
||||
102,7.1,3.0,5.9,2.1,virginica,3
|
||||
103,6.3,2.9,5.6,1.8,virginica,3
|
||||
104,6.5,3.0,5.8,2.2,virginica,3
|
||||
105,7.6,3.0,6.6,2.1,virginica,3
|
||||
106,4.9,2.5,4.5,1.7,virginica,3
|
||||
107,7.3,2.9,6.3,1.8,virginica,3
|
||||
108,6.7,2.5,5.8,1.8,virginica,3
|
||||
109,7.2,3.6,6.1,2.5,virginica,3
|
||||
110,6.5,3.2,5.1,2.0,virginica,3
|
||||
111,6.4,2.7,5.3,1.9,virginica,3
|
||||
112,6.8,3.0,5.5,2.1,virginica,3
|
||||
113,5.7,2.5,5.0,2.0,virginica,3
|
||||
114,5.8,2.8,5.1,2.4,virginica,3
|
||||
115,6.4,3.2,5.3,2.3,virginica,3
|
||||
116,6.5,3.0,5.5,1.8,virginica,3
|
||||
117,7.7,3.8,6.7,2.2,virginica,3
|
||||
118,7.7,2.6,6.9,2.3,virginica,3
|
||||
119,6.0,2.2,5.0,1.5,virginica,3
|
||||
120,6.9,3.2,5.7,2.3,virginica,3
|
||||
121,5.6,2.8,4.9,2.0,virginica,3
|
||||
122,7.7,2.8,6.7,2.0,virginica,3
|
||||
123,6.3,2.7,4.9,1.8,virginica,3
|
||||
124,6.7,3.3,5.7,2.1,virginica,3
|
||||
125,7.2,3.2,6.0,1.8,virginica,3
|
||||
126,6.2,2.8,4.8,1.8,virginica,3
|
||||
127,6.1,3.0,4.9,1.8,virginica,3
|
||||
128,6.4,2.8,5.6,2.1,virginica,3
|
||||
129,7.2,3.0,5.8,1.6,virginica,3
|
||||
130,7.4,2.8,6.1,1.9,virginica,3
|
||||
131,7.9,3.8,6.4,2.0,virginica,3
|
||||
132,6.4,2.8,5.6,2.2,virginica,3
|
||||
133,6.3,2.8,5.1,1.5,virginica,3
|
||||
134,6.1,2.6,5.6,1.4,virginica,3
|
||||
135,7.7,3.0,6.1,2.3,virginica,3
|
||||
136,6.3,3.4,5.6,2.4,virginica,3
|
||||
137,6.4,3.1,5.5,1.8,virginica,3
|
||||
138,6.0,3.0,4.8,1.8,virginica,3
|
||||
139,6.9,3.1,5.4,2.1,virginica,3
|
||||
140,6.7,3.1,5.6,2.4,virginica,3
|
||||
141,6.9,3.1,5.1,2.3,virginica,3
|
||||
142,5.8,2.7,5.1,1.9,virginica,3
|
||||
143,6.8,3.2,5.9,2.3,virginica,3
|
||||
144,6.7,3.3,5.7,2.5,virginica,3
|
||||
145,6.7,3.0,5.2,2.3,virginica,3
|
||||
146,6.3,2.5,5.0,1.9,virginica,3
|
||||
147,6.5,3.0,5.2,2.0,virginica,3
|
||||
148,6.2,3.4,5.4,2.3,virginica,3
|
||||
149,5.9,3.0,5.1,1.8,virginica,3
|
||||
|
|
|
@ -0,0 +1,10 @@
|
|||
,nation,medal,count
|
||||
0,South Korea,gold,24
|
||||
1,China,gold,10
|
||||
2,Canada,gold,9
|
||||
3,South Korea,silver,13
|
||||
4,China,silver,15
|
||||
5,Canada,silver,12
|
||||
6,South Korea,bronze,11
|
||||
7,China,bronze,8
|
||||
8,Canada,bronze,12
|
||||
|
|
|
@ -0,0 +1,4 @@
|
|||
,nation,gold,silver,bronze
|
||||
0,South Korea,24,13,11
|
||||
1,China,10,15,8
|
||||
2,Canada,9,12,12
|
||||
|
|
|
@ -0,0 +1,34 @@
|
|||
import plotly.express as px
|
||||
import pandas
|
||||
df = px.data.gapminder()
|
||||
df.to_csv("gapminder.csv")
|
||||
|
||||
df = px.data.tips()
|
||||
df.to_csv("tips.csv")
|
||||
|
||||
df = px.data.wind()
|
||||
df.to_csv("wind.csv")
|
||||
|
||||
df = px.data.iris()
|
||||
df.to_csv("iris.csv")
|
||||
|
||||
df = px.data.stocks()
|
||||
df.to_csv("stocks.csv")
|
||||
|
||||
df = px.data.carshare()
|
||||
df.to_csv("carshare.csv")
|
||||
|
||||
df = px.data.election()
|
||||
df.to_csv("election.csv")
|
||||
|
||||
# df = px.data.election_geojson()
|
||||
# df.to_csv("election_geojson.csv")
|
||||
|
||||
df = px.data.experiment()
|
||||
df.to_csv("experiment.csv")
|
||||
|
||||
df = px.data.medals_long()
|
||||
df.to_csv("medals_long.csv")
|
||||
|
||||
df = px.data.medals_wide()
|
||||
df.to_csv("medals_wide.csv")
|
||||
|
|
@ -1,4 +1,10 @@
|
|||
1 教学视频 express
|
||||
https://www.bilibili.com/video/BV1iW4y1M7v7/?spm_id_from=333.337.search-card.all.click&vd_source=311a862c74a77082f872d2e1ab5d1523
|
||||
2 教学视频 go
|
||||
https://www.bilibili.com/video/BV13E411Z7XH?p=2&vd_source=311a862c74a77082f872d2e1ab5d1523
|
||||
https://www.bilibili.com/video/BV13E411Z7XH?p=2&vd_source=311a862c74a77082f872d2e1ab5d1523
|
||||
3 plotly官网
|
||||
https://plotly.com/python/
|
||||
4 data 介绍
|
||||
https://www.finclip.com/news/f/3709.html
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -0,0 +1,106 @@
|
|||
,date,GOOG,AAPL,AMZN,FB,NFLX,MSFT
|
||||
0,2018-01-01,1.0,1.0,1.0,1.0,1.0,1.0
|
||||
1,2018-01-08,1.018172278347936,1.0119428342857142,1.0618806117055757,0.9599678310954936,1.0535263142643383,1.015988161560536
|
||||
2,2018-01-15,1.032007866452698,1.0197714685714288,1.0532404284307677,0.9702434422185674,1.0498595254569378,1.0205238457756245
|
||||
3,2018-01-22,1.066782783389724,0.9800571142857144,1.1406756202628388,1.0168584099483515,1.3076813155940448,1.0665607876956391
|
||||
4,2018-01-29,1.0087731636550117,0.9171428571428571,1.1633743377885228,1.0183569327795472,1.273536771428717,1.040707528275144
|
||||
5,2018-02-05,0.9415276737437316,0.8937714514285715,1.0898676795580526,0.9425207136466456,1.188008929282134,0.9998865857832728
|
||||
6,2018-02-12,0.99325918262539,0.9853142457142856,1.1786207619316666,0.949210571606832,1.3263487897912096,1.043202153459527
|
||||
7,2018-02-19,1.0222821547641083,1.002857142857143,1.2203654438831366,0.9809472149548658,1.3616362026373592,1.0665607876956391
|
||||
8,2018-02-26,0.9788520214265992,1.006914325714286,1.2205688381237838,0.9452501435830832,1.4336396058469547,1.0551082990110374
|
||||
9,2018-03-05,1.0524482730908842,1.02845712,1.284548542665418,0.9913298905647344,1.5783608462698024,1.0946819232411402
|
||||
10,2018-03-12,1.0303929312465263,1.0172571657142857,1.2786826844946546,0.9905806264731936,1.5165008067883996,1.072683930770293
|
||||
11,2018-03-19,0.926821104067592,0.9425142971428572,1.2167532101702832,0.8530371628674177,1.4331158380609592,0.9885474319413214
|
||||
12,2018-03-26,0.9360932452590338,0.9587428514285714,1.1775224533715958,0.8551778853033591,1.406495542490225,1.034924537137441
|
||||
13,2018-04-02,0.913638710861412,0.9621714571428572,1.1432627388670606,0.8413165210173983,1.375541688281783,1.0231318851767346
|
||||
14,2018-04-09,0.93380695379017,0.99845712,1.16405781403187,0.8804923666954552,1.484118227436587,1.0554484622871425
|
||||
15,2018-04-16,0.9734447261178653,0.9469714342857144,1.242730666448932,0.8899116599439659,1.5608837620628662,1.0772196149853812
|
||||
16,2018-04-23,0.9345146364100892,0.9275428971428572,1.2794473988384474,0.9290339332394776,1.484642138086525,1.0865177211357813
|
||||
17,2018-04-30,0.9509902470625956,1.0504571542857144,1.2862244591394254,0.9451966568307202,1.5243106261176576,1.0790339249567087
|
||||
18,2018-05-07,0.9963982380519172,1.07765712,1.3040906767647622,1.0007492587396545,1.5546453794312736,1.1078352963411884
|
||||
19,2018-05-14,0.9674568868105002,1.06462856,1.2808711585229775,0.9776825642702948,1.5437877293254985,1.0926408755495889
|
||||
20,2018-05-21,0.9758943718805396,1.0776000114285715,1.3099809658381354,0.9896708164943808,1.6728891882258874,1.1153191832334917
|
||||
21,2018-05-28,1.015668254641377,1.0870857428571428,1.3355191588974509,1.038212463316699,1.7140339274719294,1.1428733270694336
|
||||
22,2018-06-04,1.0169111849053498,1.0954285542857145,1.3700554610940725,1.0120417443283358,1.7170817582484463,1.1523981709400573
|
||||
23,2018-06-11,1.0453898287179595,1.0790856914285714,1.3960736368996989,1.048166977313343,1.866660325094997,1.1353894401771305
|
||||
24,2018-06-18,1.0483111519067918,1.0566857028571428,1.3958296232020404,1.0796895826698554,1.9576645850358447,1.1385644826269534
|
||||
25,2018-06-25,1.0121753574512644,1.0577714342857143,1.3829181608736414,1.039978596521961,1.864041067097456,1.1181539716939797
|
||||
26,2018-07-02,1.0344211867653972,1.0741142914285715,1.391729163581091,1.0876638451914205,1.94414015086099,1.147068848008417
|
||||
27,2018-07-09,1.0785588920381208,1.093314297142857,1.4750394640760272,1.109553119307901,1.884851557577705,1.1954869895569342
|
||||
28,2018-07-16,1.075011617811375,1.0939428685714283,1.4755844971819587,1.12357503483302,1.7193674908479577,1.2050118447667115
|
||||
29,2018-07-23,1.1236312044424703,1.0913142628571428,1.4784890230752108,0.9359914015737306,1.691556657660921,1.2210000857013248
|
||||
30,2018-07-30,1.1102129167272332,1.1885143142857142,1.4833867718479574,0.951458353177682,1.633839648701375,1.225082192423581
|
||||
31,2018-08-06,1.1228237368393843,1.1858857085714285,1.5346502643964448,0.9647310099631464,1.647078369277624,1.2359677687727004
|
||||
32,2018-08-13,1.0895729410299655,1.2433142971428572,1.5313308069300795,0.9301578668399936,1.50854798541483,1.2198661929954373
|
||||
33,2018-08-20,1.1074367837463466,1.235200022857143,1.5501814209506477,0.934706922085943,1.7087480282692504,1.2291642991458374
|
||||
34,2018-08-27,1.1052048693141154,1.3007428857142855,1.637494456642517,0.940486970067317,1.7509404459512254,1.2737271737447062
|
||||
35,2018-09-03,1.0567939333314087,1.2645714457142856,1.5881591374274802,0.8725715159998442,1.660459949034241,1.227009825898405
|
||||
36,2018-09-10,1.0637798374890872,1.279085691428571,1.6029011479217037,0.868718232741186,1.7360826197418304,1.2855199050794894
|
||||
37,2018-09-17,1.0579370795194665,1.2437714514285716,1.5580080272628667,0.8719828084993478,1.720034255916133,1.2956117406596723
|
||||
38,2018-09-24,1.0827776350267664,1.2899428857142856,1.6295946560652816,0.8801712695690254,1.7816562507344105,1.2968590589214408
|
||||
39,2018-10-01,1.0500077089175164,1.2816571028571428,1.5373757268816928,0.8420122930046896,1.6731749018244944,1.2714592862805467
|
||||
40,2018-10-08,1.007121903906116,1.2692000057142856,1.4551718788522234,0.822799036998693,1.617029334324746,1.242431086462613
|
||||
41,2018-10-15,0.9947651405743836,1.253199988571429,1.435174192909178,0.8244581110690464,1.5842183202957685,1.2321125018230523
|
||||
42,2018-10-22,0.9720929301886708,1.236000017142857,1.3365524179114776,0.7780036945784202,1.4278298007564696,1.2128358835959658
|
||||
43,2018-10-29,0.959681788913054,1.1855999771428571,1.3550368620941855,0.8046561475625534,1.4719748494696214,1.203764617218174
|
||||
44,2018-11-05,0.9672663993407256,1.1684000057142856,1.3931936419790223,0.7758094853901156,1.4451640257830367,1.242431086462613
|
||||
45,2018-11-12,0.9630385756700248,1.1058857085714286,1.2963616956201691,0.7467486995959743,1.3629695899097676,1.2279169808840689
|
||||
46,2018-11-19,0.9289168536315806,0.9845142457142856,1.22204146042711,0.7050039698687512,1.2325348866009125,1.1687265864899288
|
||||
47,2018-11-26,0.992923504040418,1.0204571542857144,1.375083410656027,0.7525287475773482,1.3625886860662726,1.2573987581948347
|
||||
48,2018-12-03,0.9404389054995582,0.9628000285714284,1.3254226411301075,0.735456214007293,1.262631595251403,1.1885701057133435
|
||||
49,2018-12-10,0.945446952912676,0.9455999771428572,1.295141330176286,0.7709927394918039,1.2707271281792676,1.2022904705229511
|
||||
50,2018-12-17,0.8886892896888904,0.8613142628571429,1.1206615472526131,0.668718185644586,1.1733415549944868,1.1138451159123457
|
||||
51,2018-12-24,0.9408925313390586,0.8927428342857143,1.202483038516975,0.712871248181817,1.2194865512765718,1.1383376428543452
|
||||
52,2018-12-31,0.9714034098401132,0.8471999714285714,1.2817010232963573,0.7382927084305257,1.4170674789973934,1.1557999511101045
|
||||
53,2019-01-07,0.9591373489949891,0.8702285314285714,1.334721869745653,0.769601275795517,1.6076479259096166,1.1656650489700635
|
||||
54,2019-01-14,0.9963982380519172,0.8961143257142857,1.3799892040777797,0.8029969932139043,1.6148387919701228,1.2213402489774292
|
||||
55,2019-01-21,0.989802500200548,0.9014856857142858,1.359137222458745,0.7974845609584834,1.6098384682642397,1.2152170945636216
|
||||
56,2019-01-28,1.0077298024501202,0.95154288,1.3230632475991762,0.8868611275292119,1.6184103905326357,1.1654382205366092
|
||||
57,2019-02-04,0.9934950771344468,0.9737714514285716,1.2921391799289847,0.8955311566861818,1.6551740498315624,1.1982083638006946
|
||||
58,2019-02-11,1.0103608540932627,0.97382856,1.3081910371293215,0.8696815348242483,1.699461814861141,1.2271232401151322
|
||||
59,2019-02-18,1.0073850422758417,0.9884000057142855,1.3273996770823542,0.8664168787877908,1.7287488945009553,1.2583059131804986
|
||||
60,2019-02-25,1.035165084150587,0.9998285771428572,1.3600809993969647,0.8685041144713691,1.7016048311442251,1.275994970495635
|
||||
61,2019-03-04,1.0363716889645844,0.9880571657142858,1.3186455808291295,0.907679960149426,1.6648411718452985,1.2530899137523548
|
||||
62,2019-03-11,1.0746032883264525,1.0635428285714286,1.393136635454831,0.8883060779778621,1.721319979015192,1.3143213671771998
|
||||
63,2019-03-18,1.0936918990354445,1.0917143028571428,1.435776232539301,0.8795289843340972,1.7191771103581814,1.3272479912178707
|
||||
64,2019-03-25,1.064487521016258,1.0854285542857145,1.4487771761299302,0.8921059494105662,1.6979855684083631,1.3373398267980536
|
||||
65,2019-04-01,1.095188886079836,1.1257142857142857,1.4947687054188046,0.9404334779630672,1.7405113638622944,1.3594511427723972
|
||||
66,2019-04-08,1.1049145977684258,1.1363999714285713,1.4994712046698764,0.9585228806468435,1.6721748970861734,1.371470623166558
|
||||
67,2019-04-15,1.1216987538299403,1.1649142914285715,1.5146280474808236,0.9541342963617566,1.716034084574645,1.398911443499003
|
||||
68,2019-04-22,1.1541874899828073,1.1674285885714286,1.5869876346023932,1.024832747396326,1.7850849901165535,1.4728426811919109
|
||||
69,2019-04-29,1.075456162061569,1.21,1.596612214272432,1.0461332337340143,1.8335634546034707,1.4616168621926098
|
||||
70,2019-05-06,1.0562859304552756,1.126742817142857,1.537644171481961,1.0079742571696786,1.7193199695385504,1.4415465939098175
|
||||
71,2019-05-13,1.0544986709579427,1.08,1.5205753430783882,0.9917045600737096,1.6879375377890014,1.45220551191279
|
||||
72,2019-05-20,1.0283425342867192,1.02268572,1.483378627942562,0.9690125351133252,1.6876518241903944,1.4314547583296346
|
||||
73,2019-05-27,1.001270175031893,1.00040004,1.44415601504927,0.9497992791073284,1.6347444679569396,1.4024265471725468
|
||||
74,2019-06-03,0.9671666152648106,1.0865713942857145,1.4677172714127285,0.9277495340299856,1.7185103405278743,1.489964746797488
|
||||
75,2019-06-10,0.98468558802946,1.1013714571428572,1.521120475440709,0.9704575658402708,1.6178389585732904,1.5018708923489987
|
||||
76,2019-06-17,1.0178275181736574,1.135885708571429,1.5549896884611636,1.0229595550561554,1.758226497494488,1.5531239130712344
|
||||
77,2019-06-24,0.980657443195294,1.130971417142857,1.540613747734834,1.0329140690527994,1.7492261453110591,1.518993128041884
|
||||
78,2019-07-01,1.0266368965939394,1.167028548571429,1.58070684404494,1.0511104505931883,1.8122290534732837,1.5541444028995486
|
||||
79,2019-07-08,1.0387124690620373,1.1617143028571428,1.6361032717659916,1.0964409334832987,1.7774655512770718,1.5750084006121237
|
||||
80,2019-07-15,1.025285100664745,1.15765712,1.5982882308164057,1.0616001853379655,1.5005476379697218,1.5491551411916282
|
||||
81,2019-07-22,1.1344366027859267,1.1870857428571429,1.5808207570233568,1.0690393020378066,1.5990284823318142,1.6026759586647925
|
||||
82,2019-07-29,1.0832494231376286,1.1658285942857145,1.4833460531345568,1.011613582715111,1.518310297673454,1.5523300929282209
|
||||
83,2019-08-05,1.0778240762422375,1.1485143142857142,1.4706054102388,1.0053518863681492,1.471165225221077,1.5615149549492018
|
||||
84,2019-08-12,1.068379555417282,1.18,1.4583936118945735,0.9831415097733526,1.4419733358261506,1.5435990692006107
|
||||
85,2019-08-19,1.0445098208996275,1.1579428514285717,1.4234505212166575,0.951297801938524,1.3878755896024673,1.5125297196387406
|
||||
86,2019-08-26,1.0779056980467905,1.1928000285714286,1.445148654606286,0.993684731270493,1.398876103650743,1.5632157599905712
|
||||
87,2019-09-02,1.0931748145700046,1.218628542857143,1.491701504811883,1.003425201923729,1.381827735086725,1.5772763674503605
|
||||
88,2019-09-09,1.12459294475006,1.25,1.4964446227063888,1.0018196199576253,1.400780927644628,1.5570926849508404
|
||||
89,2019-09-16,1.115856106545024,1.2441714057142856,1.4596872708598625,1.0164837404393767,1.2893470810670251,1.581131634400008
|
||||
90,2019-09-23,1.1114649285805127,1.25040004,1.4037863302335007,0.9478191079105452,1.2528214711933554,1.5617416132953483
|
||||
91,2019-09-30,1.0968672799119472,1.2971999714285716,1.4153391824933792,0.9657478790768677,1.299061872016242,1.5661638719545554
|
||||
92,2019-10-07,1.10271900878617,1.3497714685714286,1.4090502488441077,0.9857639608531776,1.347349808387309,1.583852929269692
|
||||
93,2019-10-14,1.129972884606169,1.3509143085714286,1.4298696556551374,0.9946481136318508,1.3110147218673576,1.5581131747791548
|
||||
94,2019-10-21,1.1477913211905195,1.409028582857143,1.43297747571907,1.0055659243596704,1.3182532521012131,1.5957590748212025
|
||||
95,2019-10-28,1.155602744537941,1.4618286114285712,1.4574742658589632,1.03623221184162,1.3658269020946976,1.629663201504406
|
||||
96,2019-11-04,1.189742629754999,1.4865143714285716,1.452950830015895,1.0213539730900516,1.388494690497293,1.655062974145301
|
||||
97,2019-11-11,1.2110630442115171,1.5186286285714288,1.4152089825177483,1.044153062537231,1.4049716271019663,1.7005329130166025
|
||||
98,2019-11-18,1.1751993590303178,1.4958857085714288,1.420277551536714,1.0640620851786324,1.4785466146353017,1.6962239778608914
|
||||
99,2019-11-25,1.183927115646047,1.5271428571428571,1.465089434095106,1.0791543619217223,1.4984522906221185,1.7165211652903694
|
||||
100,2019-12-02,1.216279741365772,1.5469142342857145,1.425061388144621,1.07599677037206,1.4636411194904255,1.720716595516122
|
||||
101,2019-12-09,1.222820990588552,1.57228568,1.4326601685000062,1.0388546682733315,1.421496227879989,1.7522394318575931
|
||||
102,2019-12-16,1.22441776261611,1.5968000114285714,1.4534552436648156,1.104094173804843,1.6043620457078422,1.7848962516181823
|
||||
103,2019-12-23,1.2265044859331442,1.6559999314285714,1.52122624451373,1.113727585323171,1.567169808867808,1.8024719740906685
|
||||
104,2019-12-30,1.213013658002661,1.6779999657142857,1.503360026888393,1.0984746770626277,1.5408828958311611,1.7881845268582712
|
||||
|
|
|
@ -0,0 +1,245 @@
|
|||
,total_bill,tip,sex,smoker,day,time,size
|
||||
0,16.99,1.01,Female,No,Sun,Dinner,2
|
||||
1,10.34,1.66,Male,No,Sun,Dinner,3
|
||||
2,21.01,3.5,Male,No,Sun,Dinner,3
|
||||
3,23.68,3.31,Male,No,Sun,Dinner,2
|
||||
4,24.59,3.61,Female,No,Sun,Dinner,4
|
||||
5,25.29,4.71,Male,No,Sun,Dinner,4
|
||||
6,8.77,2.0,Male,No,Sun,Dinner,2
|
||||
7,26.88,3.12,Male,No,Sun,Dinner,4
|
||||
8,15.04,1.96,Male,No,Sun,Dinner,2
|
||||
9,14.78,3.23,Male,No,Sun,Dinner,2
|
||||
10,10.27,1.71,Male,No,Sun,Dinner,2
|
||||
11,35.26,5.0,Female,No,Sun,Dinner,4
|
||||
12,15.42,1.57,Male,No,Sun,Dinner,2
|
||||
13,18.43,3.0,Male,No,Sun,Dinner,4
|
||||
14,14.83,3.02,Female,No,Sun,Dinner,2
|
||||
15,21.58,3.92,Male,No,Sun,Dinner,2
|
||||
16,10.33,1.67,Female,No,Sun,Dinner,3
|
||||
17,16.29,3.71,Male,No,Sun,Dinner,3
|
||||
18,16.97,3.5,Female,No,Sun,Dinner,3
|
||||
19,20.65,3.35,Male,No,Sat,Dinner,3
|
||||
20,17.92,4.08,Male,No,Sat,Dinner,2
|
||||
21,20.29,2.75,Female,No,Sat,Dinner,2
|
||||
22,15.77,2.23,Female,No,Sat,Dinner,2
|
||||
23,39.42,7.58,Male,No,Sat,Dinner,4
|
||||
24,19.82,3.18,Male,No,Sat,Dinner,2
|
||||
25,17.81,2.34,Male,No,Sat,Dinner,4
|
||||
26,13.37,2.0,Male,No,Sat,Dinner,2
|
||||
27,12.69,2.0,Male,No,Sat,Dinner,2
|
||||
28,21.7,4.3,Male,No,Sat,Dinner,2
|
||||
29,19.65,3.0,Female,No,Sat,Dinner,2
|
||||
30,9.55,1.45,Male,No,Sat,Dinner,2
|
||||
31,18.35,2.5,Male,No,Sat,Dinner,4
|
||||
32,15.06,3.0,Female,No,Sat,Dinner,2
|
||||
33,20.69,2.45,Female,No,Sat,Dinner,4
|
||||
34,17.78,3.27,Male,No,Sat,Dinner,2
|
||||
35,24.06,3.6,Male,No,Sat,Dinner,3
|
||||
36,16.31,2.0,Male,No,Sat,Dinner,3
|
||||
37,16.93,3.07,Female,No,Sat,Dinner,3
|
||||
38,18.69,2.31,Male,No,Sat,Dinner,3
|
||||
39,31.27,5.0,Male,No,Sat,Dinner,3
|
||||
40,16.04,2.24,Male,No,Sat,Dinner,3
|
||||
41,17.46,2.54,Male,No,Sun,Dinner,2
|
||||
42,13.94,3.06,Male,No,Sun,Dinner,2
|
||||
43,9.68,1.32,Male,No,Sun,Dinner,2
|
||||
44,30.4,5.6,Male,No,Sun,Dinner,4
|
||||
45,18.29,3.0,Male,No,Sun,Dinner,2
|
||||
46,22.23,5.0,Male,No,Sun,Dinner,2
|
||||
47,32.4,6.0,Male,No,Sun,Dinner,4
|
||||
48,28.55,2.05,Male,No,Sun,Dinner,3
|
||||
49,18.04,3.0,Male,No,Sun,Dinner,2
|
||||
50,12.54,2.5,Male,No,Sun,Dinner,2
|
||||
51,10.29,2.6,Female,No,Sun,Dinner,2
|
||||
52,34.81,5.2,Female,No,Sun,Dinner,4
|
||||
53,9.94,1.56,Male,No,Sun,Dinner,2
|
||||
54,25.56,4.34,Male,No,Sun,Dinner,4
|
||||
55,19.49,3.51,Male,No,Sun,Dinner,2
|
||||
56,38.01,3.0,Male,Yes,Sat,Dinner,4
|
||||
57,26.41,1.5,Female,No,Sat,Dinner,2
|
||||
58,11.24,1.76,Male,Yes,Sat,Dinner,2
|
||||
59,48.27,6.73,Male,No,Sat,Dinner,4
|
||||
60,20.29,3.21,Male,Yes,Sat,Dinner,2
|
||||
61,13.81,2.0,Male,Yes,Sat,Dinner,2
|
||||
62,11.02,1.98,Male,Yes,Sat,Dinner,2
|
||||
63,18.29,3.76,Male,Yes,Sat,Dinner,4
|
||||
64,17.59,2.64,Male,No,Sat,Dinner,3
|
||||
65,20.08,3.15,Male,No,Sat,Dinner,3
|
||||
66,16.45,2.47,Female,No,Sat,Dinner,2
|
||||
67,3.07,1.0,Female,Yes,Sat,Dinner,1
|
||||
68,20.23,2.01,Male,No,Sat,Dinner,2
|
||||
69,15.01,2.09,Male,Yes,Sat,Dinner,2
|
||||
70,12.02,1.97,Male,No,Sat,Dinner,2
|
||||
71,17.07,3.0,Female,No,Sat,Dinner,3
|
||||
72,26.86,3.14,Female,Yes,Sat,Dinner,2
|
||||
73,25.28,5.0,Female,Yes,Sat,Dinner,2
|
||||
74,14.73,2.2,Female,No,Sat,Dinner,2
|
||||
75,10.51,1.25,Male,No,Sat,Dinner,2
|
||||
76,17.92,3.08,Male,Yes,Sat,Dinner,2
|
||||
77,27.2,4.0,Male,No,Thur,Lunch,4
|
||||
78,22.76,3.0,Male,No,Thur,Lunch,2
|
||||
79,17.29,2.71,Male,No,Thur,Lunch,2
|
||||
80,19.44,3.0,Male,Yes,Thur,Lunch,2
|
||||
81,16.66,3.4,Male,No,Thur,Lunch,2
|
||||
82,10.07,1.83,Female,No,Thur,Lunch,1
|
||||
83,32.68,5.0,Male,Yes,Thur,Lunch,2
|
||||
84,15.98,2.03,Male,No,Thur,Lunch,2
|
||||
85,34.83,5.17,Female,No,Thur,Lunch,4
|
||||
86,13.03,2.0,Male,No,Thur,Lunch,2
|
||||
87,18.28,4.0,Male,No,Thur,Lunch,2
|
||||
88,24.71,5.85,Male,No,Thur,Lunch,2
|
||||
89,21.16,3.0,Male,No,Thur,Lunch,2
|
||||
90,28.97,3.0,Male,Yes,Fri,Dinner,2
|
||||
91,22.49,3.5,Male,No,Fri,Dinner,2
|
||||
92,5.75,1.0,Female,Yes,Fri,Dinner,2
|
||||
93,16.32,4.3,Female,Yes,Fri,Dinner,2
|
||||
94,22.75,3.25,Female,No,Fri,Dinner,2
|
||||
95,40.17,4.73,Male,Yes,Fri,Dinner,4
|
||||
96,27.28,4.0,Male,Yes,Fri,Dinner,2
|
||||
97,12.03,1.5,Male,Yes,Fri,Dinner,2
|
||||
98,21.01,3.0,Male,Yes,Fri,Dinner,2
|
||||
99,12.46,1.5,Male,No,Fri,Dinner,2
|
||||
100,11.35,2.5,Female,Yes,Fri,Dinner,2
|
||||
101,15.38,3.0,Female,Yes,Fri,Dinner,2
|
||||
102,44.3,2.5,Female,Yes,Sat,Dinner,3
|
||||
103,22.42,3.48,Female,Yes,Sat,Dinner,2
|
||||
104,20.92,4.08,Female,No,Sat,Dinner,2
|
||||
105,15.36,1.64,Male,Yes,Sat,Dinner,2
|
||||
106,20.49,4.06,Male,Yes,Sat,Dinner,2
|
||||
107,25.21,4.29,Male,Yes,Sat,Dinner,2
|
||||
108,18.24,3.76,Male,No,Sat,Dinner,2
|
||||
109,14.31,4.0,Female,Yes,Sat,Dinner,2
|
||||
110,14.0,3.0,Male,No,Sat,Dinner,2
|
||||
111,7.25,1.0,Female,No,Sat,Dinner,1
|
||||
112,38.07,4.0,Male,No,Sun,Dinner,3
|
||||
113,23.95,2.55,Male,No,Sun,Dinner,2
|
||||
114,25.71,4.0,Female,No,Sun,Dinner,3
|
||||
115,17.31,3.5,Female,No,Sun,Dinner,2
|
||||
116,29.93,5.07,Male,No,Sun,Dinner,4
|
||||
117,10.65,1.5,Female,No,Thur,Lunch,2
|
||||
118,12.43,1.8,Female,No,Thur,Lunch,2
|
||||
119,24.08,2.92,Female,No,Thur,Lunch,4
|
||||
120,11.69,2.31,Male,No,Thur,Lunch,2
|
||||
121,13.42,1.68,Female,No,Thur,Lunch,2
|
||||
122,14.26,2.5,Male,No,Thur,Lunch,2
|
||||
123,15.95,2.0,Male,No,Thur,Lunch,2
|
||||
124,12.48,2.52,Female,No,Thur,Lunch,2
|
||||
125,29.8,4.2,Female,No,Thur,Lunch,6
|
||||
126,8.52,1.48,Male,No,Thur,Lunch,2
|
||||
127,14.52,2.0,Female,No,Thur,Lunch,2
|
||||
128,11.38,2.0,Female,No,Thur,Lunch,2
|
||||
129,22.82,2.18,Male,No,Thur,Lunch,3
|
||||
130,19.08,1.5,Male,No,Thur,Lunch,2
|
||||
131,20.27,2.83,Female,No,Thur,Lunch,2
|
||||
132,11.17,1.5,Female,No,Thur,Lunch,2
|
||||
133,12.26,2.0,Female,No,Thur,Lunch,2
|
||||
134,18.26,3.25,Female,No,Thur,Lunch,2
|
||||
135,8.51,1.25,Female,No,Thur,Lunch,2
|
||||
136,10.33,2.0,Female,No,Thur,Lunch,2
|
||||
137,14.15,2.0,Female,No,Thur,Lunch,2
|
||||
138,16.0,2.0,Male,Yes,Thur,Lunch,2
|
||||
139,13.16,2.75,Female,No,Thur,Lunch,2
|
||||
140,17.47,3.5,Female,No,Thur,Lunch,2
|
||||
141,34.3,6.7,Male,No,Thur,Lunch,6
|
||||
142,41.19,5.0,Male,No,Thur,Lunch,5
|
||||
143,27.05,5.0,Female,No,Thur,Lunch,6
|
||||
144,16.43,2.3,Female,No,Thur,Lunch,2
|
||||
145,8.35,1.5,Female,No,Thur,Lunch,2
|
||||
146,18.64,1.36,Female,No,Thur,Lunch,3
|
||||
147,11.87,1.63,Female,No,Thur,Lunch,2
|
||||
148,9.78,1.73,Male,No,Thur,Lunch,2
|
||||
149,7.51,2.0,Male,No,Thur,Lunch,2
|
||||
150,14.07,2.5,Male,No,Sun,Dinner,2
|
||||
151,13.13,2.0,Male,No,Sun,Dinner,2
|
||||
152,17.26,2.74,Male,No,Sun,Dinner,3
|
||||
153,24.55,2.0,Male,No,Sun,Dinner,4
|
||||
154,19.77,2.0,Male,No,Sun,Dinner,4
|
||||
155,29.85,5.14,Female,No,Sun,Dinner,5
|
||||
156,48.17,5.0,Male,No,Sun,Dinner,6
|
||||
157,25.0,3.75,Female,No,Sun,Dinner,4
|
||||
158,13.39,2.61,Female,No,Sun,Dinner,2
|
||||
159,16.49,2.0,Male,No,Sun,Dinner,4
|
||||
160,21.5,3.5,Male,No,Sun,Dinner,4
|
||||
161,12.66,2.5,Male,No,Sun,Dinner,2
|
||||
162,16.21,2.0,Female,No,Sun,Dinner,3
|
||||
163,13.81,2.0,Male,No,Sun,Dinner,2
|
||||
164,17.51,3.0,Female,Yes,Sun,Dinner,2
|
||||
165,24.52,3.48,Male,No,Sun,Dinner,3
|
||||
166,20.76,2.24,Male,No,Sun,Dinner,2
|
||||
167,31.71,4.5,Male,No,Sun,Dinner,4
|
||||
168,10.59,1.61,Female,Yes,Sat,Dinner,2
|
||||
169,10.63,2.0,Female,Yes,Sat,Dinner,2
|
||||
170,50.81,10.0,Male,Yes,Sat,Dinner,3
|
||||
171,15.81,3.16,Male,Yes,Sat,Dinner,2
|
||||
172,7.25,5.15,Male,Yes,Sun,Dinner,2
|
||||
173,31.85,3.18,Male,Yes,Sun,Dinner,2
|
||||
174,16.82,4.0,Male,Yes,Sun,Dinner,2
|
||||
175,32.9,3.11,Male,Yes,Sun,Dinner,2
|
||||
176,17.89,2.0,Male,Yes,Sun,Dinner,2
|
||||
177,14.48,2.0,Male,Yes,Sun,Dinner,2
|
||||
178,9.6,4.0,Female,Yes,Sun,Dinner,2
|
||||
179,34.63,3.55,Male,Yes,Sun,Dinner,2
|
||||
180,34.65,3.68,Male,Yes,Sun,Dinner,4
|
||||
181,23.33,5.65,Male,Yes,Sun,Dinner,2
|
||||
182,45.35,3.5,Male,Yes,Sun,Dinner,3
|
||||
183,23.17,6.5,Male,Yes,Sun,Dinner,4
|
||||
184,40.55,3.0,Male,Yes,Sun,Dinner,2
|
||||
185,20.69,5.0,Male,No,Sun,Dinner,5
|
||||
186,20.9,3.5,Female,Yes,Sun,Dinner,3
|
||||
187,30.46,2.0,Male,Yes,Sun,Dinner,5
|
||||
188,18.15,3.5,Female,Yes,Sun,Dinner,3
|
||||
189,23.1,4.0,Male,Yes,Sun,Dinner,3
|
||||
190,15.69,1.5,Male,Yes,Sun,Dinner,2
|
||||
191,19.81,4.19,Female,Yes,Thur,Lunch,2
|
||||
192,28.44,2.56,Male,Yes,Thur,Lunch,2
|
||||
193,15.48,2.02,Male,Yes,Thur,Lunch,2
|
||||
194,16.58,4.0,Male,Yes,Thur,Lunch,2
|
||||
195,7.56,1.44,Male,No,Thur,Lunch,2
|
||||
196,10.34,2.0,Male,Yes,Thur,Lunch,2
|
||||
197,43.11,5.0,Female,Yes,Thur,Lunch,4
|
||||
198,13.0,2.0,Female,Yes,Thur,Lunch,2
|
||||
199,13.51,2.0,Male,Yes,Thur,Lunch,2
|
||||
200,18.71,4.0,Male,Yes,Thur,Lunch,3
|
||||
201,12.74,2.01,Female,Yes,Thur,Lunch,2
|
||||
202,13.0,2.0,Female,Yes,Thur,Lunch,2
|
||||
203,16.4,2.5,Female,Yes,Thur,Lunch,2
|
||||
204,20.53,4.0,Male,Yes,Thur,Lunch,4
|
||||
205,16.47,3.23,Female,Yes,Thur,Lunch,3
|
||||
206,26.59,3.41,Male,Yes,Sat,Dinner,3
|
||||
207,38.73,3.0,Male,Yes,Sat,Dinner,4
|
||||
208,24.27,2.03,Male,Yes,Sat,Dinner,2
|
||||
209,12.76,2.23,Female,Yes,Sat,Dinner,2
|
||||
210,30.06,2.0,Male,Yes,Sat,Dinner,3
|
||||
211,25.89,5.16,Male,Yes,Sat,Dinner,4
|
||||
212,48.33,9.0,Male,No,Sat,Dinner,4
|
||||
213,13.27,2.5,Female,Yes,Sat,Dinner,2
|
||||
214,28.17,6.5,Female,Yes,Sat,Dinner,3
|
||||
215,12.9,1.1,Female,Yes,Sat,Dinner,2
|
||||
216,28.15,3.0,Male,Yes,Sat,Dinner,5
|
||||
217,11.59,1.5,Male,Yes,Sat,Dinner,2
|
||||
218,7.74,1.44,Male,Yes,Sat,Dinner,2
|
||||
219,30.14,3.09,Female,Yes,Sat,Dinner,4
|
||||
220,12.16,2.2,Male,Yes,Fri,Lunch,2
|
||||
221,13.42,3.48,Female,Yes,Fri,Lunch,2
|
||||
222,8.58,1.92,Male,Yes,Fri,Lunch,1
|
||||
223,15.98,3.0,Female,No,Fri,Lunch,3
|
||||
224,13.42,1.58,Male,Yes,Fri,Lunch,2
|
||||
225,16.27,2.5,Female,Yes,Fri,Lunch,2
|
||||
226,10.09,2.0,Female,Yes,Fri,Lunch,2
|
||||
227,20.45,3.0,Male,No,Sat,Dinner,4
|
||||
228,13.28,2.72,Male,No,Sat,Dinner,2
|
||||
229,22.12,2.88,Female,Yes,Sat,Dinner,2
|
||||
230,24.01,2.0,Male,Yes,Sat,Dinner,4
|
||||
231,15.69,3.0,Male,Yes,Sat,Dinner,3
|
||||
232,11.61,3.39,Male,No,Sat,Dinner,2
|
||||
233,10.77,1.47,Male,No,Sat,Dinner,2
|
||||
234,15.53,3.0,Male,Yes,Sat,Dinner,2
|
||||
235,10.07,1.25,Male,No,Sat,Dinner,2
|
||||
236,12.6,1.0,Male,Yes,Sat,Dinner,2
|
||||
237,32.83,1.17,Male,Yes,Sat,Dinner,2
|
||||
238,35.83,4.67,Female,No,Sat,Dinner,3
|
||||
239,29.03,5.92,Male,No,Sat,Dinner,3
|
||||
240,27.18,2.0,Female,Yes,Sat,Dinner,2
|
||||
241,22.67,2.0,Male,Yes,Sat,Dinner,2
|
||||
242,17.82,1.75,Male,No,Sat,Dinner,2
|
||||
243,18.78,3.0,Female,No,Thur,Dinner,2
|
||||
|
|
|
@ -0,0 +1,129 @@
|
|||
,direction,strength,frequency
|
||||
0,N,0-1,0.5
|
||||
1,NNE,0-1,0.6
|
||||
2,NE,0-1,0.5
|
||||
3,ENE,0-1,0.4
|
||||
4,E,0-1,0.4
|
||||
5,ESE,0-1,0.3
|
||||
6,SE,0-1,0.4
|
||||
7,SSE,0-1,0.4
|
||||
8,S,0-1,0.6
|
||||
9,SSW,0-1,0.4
|
||||
10,SW,0-1,0.5
|
||||
11,WSW,0-1,0.6
|
||||
12,W,0-1,0.6
|
||||
13,WNW,0-1,0.5
|
||||
14,NW,0-1,0.4
|
||||
15,NNW,0-1,0.1
|
||||
16,N,1-2,1.6
|
||||
17,NNE,1-2,1.8
|
||||
18,NE,1-2,1.5
|
||||
19,ENE,1-2,1.6
|
||||
20,E,1-2,1.6
|
||||
21,ESE,1-2,1.2
|
||||
22,SE,1-2,1.5
|
||||
23,SSE,1-2,1.7
|
||||
24,S,1-2,2.2
|
||||
25,SSW,1-2,2.0
|
||||
26,SW,1-2,2.3
|
||||
27,WSW,1-2,2.4
|
||||
28,W,1-2,2.3
|
||||
29,WNW,1-2,2.6
|
||||
30,NW,1-2,2.3
|
||||
31,NNW,1-2,0.8
|
||||
32,N,2-3,0.9
|
||||
33,NNE,2-3,1.3
|
||||
34,NE,2-3,1.6
|
||||
35,ENE,2-3,0.9
|
||||
36,E,2-3,1.0
|
||||
37,ESE,2-3,0.6
|
||||
38,SE,2-3,0.6
|
||||
39,SSE,2-3,0.9
|
||||
40,S,2-3,1.4
|
||||
41,SSW,2-3,1.7
|
||||
42,SW,2-3,1.9
|
||||
43,WSW,2-3,2.2
|
||||
44,W,2-3,1.8
|
||||
45,WNW,2-3,1.7
|
||||
46,NW,2-3,1.8
|
||||
47,NNW,2-3,0.8
|
||||
48,N,3-4,0.9
|
||||
49,NNE,3-4,0.8
|
||||
50,NE,3-4,1.2
|
||||
51,ENE,3-4,1.0
|
||||
52,E,3-4,0.8
|
||||
53,ESE,3-4,0.4
|
||||
54,SE,3-4,0.5
|
||||
55,SSE,3-4,0.5
|
||||
56,S,3-4,0.8
|
||||
57,SSW,3-4,0.9
|
||||
58,SW,3-4,1.3
|
||||
59,WSW,3-4,1.1
|
||||
60,W,3-4,1.2
|
||||
61,WNW,3-4,1.2
|
||||
62,NW,3-4,1.3
|
||||
63,NNW,3-4,1.0
|
||||
64,N,4-4,0.4
|
||||
65,NNE,4-4,0.5
|
||||
66,NE,4-4,1.2
|
||||
67,ENE,4-4,0.5
|
||||
68,E,4-4,0.4
|
||||
69,ESE,4-4,0.2
|
||||
70,SE,4-4,0.4
|
||||
71,SSE,4-4,0.4
|
||||
72,S,4-4,0.7
|
||||
73,SSW,4-4,0.6
|
||||
74,SW,4-4,0.7
|
||||
75,WSW,4-4,0.8
|
||||
76,W,4-4,0.9
|
||||
77,WNW,4-4,1.0
|
||||
78,NW,4-4,1.0
|
||||
79,NNW,4-4,0.7
|
||||
80,N,4-5,0.3
|
||||
81,NNE,4-5,0.3
|
||||
82,NE,4-5,0.6
|
||||
83,ENE,4-5,0.2
|
||||
84,E,4-5,0.1
|
||||
85,ESE,4-5,0.1
|
||||
86,SE,4-5,0.05
|
||||
87,SSE,4-5,0.1
|
||||
88,S,4-5,0.1
|
||||
89,SSW,4-5,0.2
|
||||
90,SW,4-5,0.3
|
||||
91,WSW,4-5,0.4
|
||||
92,W,4-5,0.9
|
||||
93,WNW,4-5,0.9
|
||||
94,NW,4-5,0.9
|
||||
95,NNW,4-5,0.3
|
||||
96,N,5-6,0.2
|
||||
97,NNE,5-6,0.1
|
||||
98,NE,5-6,0.1
|
||||
99,ENE,5-6,0.1
|
||||
100,E,5-6,0.1
|
||||
101,ESE,5-6,0.1
|
||||
102,SE,5-6,0.05
|
||||
103,SSE,5-6,0.05
|
||||
104,S,5-6,0.1
|
||||
105,SSW,5-6,0.05
|
||||
106,SW,5-6,0.2
|
||||
107,WSW,5-6,0.2
|
||||
108,W,5-6,0.4
|
||||
109,WNW,5-6,0.7
|
||||
110,NW,5-6,0.7
|
||||
111,NNW,5-6,0.4
|
||||
112,N,6+,0.1
|
||||
113,NNE,6+,0.1
|
||||
114,NE,6+,0.1
|
||||
115,ENE,6+,0.1
|
||||
116,E,6+,0.1
|
||||
117,ESE,6+,0.05
|
||||
118,SE,6+,0.05
|
||||
119,SSE,6+,0.05
|
||||
120,S,6+,0.05
|
||||
121,SSW,6+,0.1
|
||||
122,SW,6+,0.1
|
||||
123,WSW,6+,0.1
|
||||
124,W,6+,0.9
|
||||
125,WNW,6+,2.2
|
||||
126,NW,6+,1.5
|
||||
127,NNW,6+,0.2
|
||||
|
Loading…
Reference in New Issue