基于一列和图的计数对数据进行排序

Question

我的数据框架中有两列：

winner    opening_shortname
0      White         Slav Defense
1      Black  Nimzowitsch Defense
2      White     King's Pawn Game
3      White    Queen's Pawn Game
4      White     Philidor Defense
...      ...                  ...
20053  White        Dutch Defense
20054  Black         Queen's Pawn
20055  White    Queen's Pawn Game
20056  White         Pirc Defense
20057  Black    Queen's Pawn Game

我想创造下面的情节，前十的开场白和它的得奖色彩比例(%)。

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Answer 1

topk = 10
z = df.groupby(['opening_shortname', 'winner']).size().unstack()
ax = z.loc[z.sum(1).sort_values().tail(topk).index].plot.barh(color=['black', 'white'], edgecolor='black')
ax.xaxis.set_visible(False)

这取决于开放的流行程度和对顶级k的限制(例如OP问题中的10 )。问题中提到的“比例(%)”是模棱两可的:所提供的地块清楚地显示从顶部开口到下一个开口的下降总数，并且水平轴被移除。

无论如何，在您提供的样本数据上：

Answer 2

假设您的dataframe是名称groupby+count+unstack. df，则可以使用然后对总数进行排序，然后用前10位来绘制：

df2 = (df.assign(count=1)
         .groupby(['winner', 'opening_shortname'])
         .count()
         .unstack(level=0)
         .droplevel(0, axis=1)
      )

# plot part
idx = df2.sum(axis=1).sort_values().head(10).index
(df2.div(df2.sum(axis=1), axis=0) # calculate the proportion
    .fillna(0)
    .loc[idx, ['White', 'Black']]
    .plot.barh(color=['w', 'k'], edgecolor='k')
)

产出：

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Answer 3

首先，您应该通过以下方法重新调整数据格式：

df = df.groupby(by = ['opening_shortname', 'winner']).size().reset_index().rename(columns = {'opening_shortname': 'opening_shortname', 'winner': 'winner', 0: 'count'}).sort_values(['count', 'opening_shortname', 'winner'], ascending = False, ignore_index = True)

因此，您将得到一个类似于(假数据)的数据：

      opening_shortname winner  count
0     Queen's Pawn Game  White    141
1     Queen's Pawn Game  Black    132
2          Queen's Pawn  White     57
3          Queen's Pawn  Black     57
4      King's Pawn Game  Black     57
5         Dutch Defense  Black     53
6      Sicilian Defense  White     51
7      Sicilian Defense  Black     50
8   Nimzowitsch Defense  White     46
9   Nimzowitsch Defense  Black     45
10     Philidor Defense  Black     44
11         Slav Defense  White     43
12         Pirc Defense  White     42
13         Slav Defense  Black     39
14         Pirc Defense  Black     38
15     King's Pawn Game  White     38
16        Dutch Defense  White     36
17     Philidor Defense  White     31

然后，您可以绘制数据，例如使用seaborn.barplot

sns.barplot(ax = ax, data = df, x = 'count', y = 'opening_shortname', hue = 'winner', palette = ['white', 'black'], edgecolor = 'black')

完整代码

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df = pd.read_csv(r'data/data.csv')

df = df.groupby(by = ['opening_shortname', 'winner']).size().reset_index().rename(columns = {'opening_shortname': 'opening_shortname', 'winner': 'winner', 0: 'count'}).sort_values(['count', 'opening_shortname', 'winner'], ascending = False, ignore_index = True)


fig, ax = plt.subplots()

sns.barplot(ax = ax, data = df, x = 'count', y = 'opening_shortname', hue = 'winner', palette = ['white', 'black'], edgecolor = 'black')

plt.show()

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如果要绘制相对比例以代替计数，则可以在上面的代码中添加一行：

df['count'] = df['count']/df.groupby('opening_shortname')['count'].transform('sum')

完整代码

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df = pd.read_csv(r'data/data.csv')

df = df.groupby(by = ['opening_shortname', 'winner']).size().reset_index().rename(columns = {'opening_shortname': 'opening_shortname', 'winner': 'winner', 0: 'count'}).sort_values(['count', 'opening_shortname', 'winner'], ascending = False, ignore_index = True)
df['count'] = df['count']/df.groupby('opening_shortname')['count'].transform('sum')


fig, ax = plt.subplots()

sns.barplot(ax = ax, data = df, x = 'count', y = 'opening_shortname', hue = 'winner', palette = ['white', 'black'], edgecolor = 'black')

plt.show()

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