pandas - 数据框中的排序/字母顺序列(Pandas)

Question

我无法按字母顺序排列数据框第一列和第二列中的名称。

数据框看起来像这样:

          Boys       Females
Rank                        
1         Michael   Jennifer
2     Christopher    Jessica
3         Matthew     Amanda
4           Jason      Sarah
5           David    Melissa
6          Joshua        Amy
7           James     Nicole
8            John  Stephanie
9          Robert  Elizabeth
10         Daniel    Heather
11         Joseph   Michelle
12         Justin    Rebecca
13           Ryan   Kimberly
14          Brian    Tiffany

我希望它看起来像这样:(男孩和女性的名字按字母顺序排列)

 Rank     Boys                 Rank    Females
 14       Brian                  3        Amanda
  2       Christopher            6        Amy
 10       Daniel                 9        Elizabeth
  5       David                 10        Heather
  7       James                  1        Jennifer

我尝试过 sort 和 sort_value 但列没有改变。这是我的原始代码

import pandas as pd



df = pd.read_html("file:///C:/Python27/babyname999.html")

df2 =df[0]  # creating a data frame from the above list of dateframes

df2.rename(columns = {'0': 'Rank', '1': 'Boys', '2': 'Females'}, inplace = True)
del df2['Unnamed: 0']

#renaming columns of dataframe


df2.set_index('Rank', inplace = True)  #setting index of dataframe to 'Rank'

我尝试过 sort 和 sort_value 但列没有改变。我不知道在哪里。有什么建议吗？

谢谢!

Answer 1

这是排序的工作示例。

import pandas as pd
from io import StringIO

data_file = StringIO(u"""Rank       Boys       Females
1         Michael   Jennifer
2     Christopher    Jessica
3         Matthew     Amanda
4           Jason      Sarah
5           David    Melissa
6          Joshua        Amy
7           James     Nicole
8            John  Stephanie
9          Robert  Elizabeth
10         Daniel    Heather
11         Joseph   Michelle
12         Justin    Rebecca
13           Ryan   Kimberly
14          Brian    Tiffany""")

df = pd.read_table(data_file, delim_whitespace=True)

boys = df[['Rank','Boys']].sort_values(['Boys']).rename(columns={'Rank': 'Rank_boys'})
females = df[['Rank','Females']].sort_values(['Females']).rename(columns={'Rank': 'Rank_females'})
result = pd.concat([boys.reset_index(drop=True), females.reset_index(drop=True)], axis=1)

结果是:

Rank_boys Boys Rank_females Females
0   14  Brian   3   Amanda
1   2   Christopher 6   Amy
2   10  Daniel  9   Elizabeth
3   5   David   10  Heather
4   7   James   1   Jennifer
5   4   Jason   2   Jessica
6   8   John    13  Kimberly
7   11  Joseph  5   Melissa
8   6   Joshua  11  Michelle
9   12  Justin  7   Nicole
10  3   Matthew 12  Rebecca
11  1   Michael 4   Sarah
12  9   Robert  8   Stephanie
13  13  Ryan    14  Tiffany