Question

我有一个名为df

的数据框

       season   seed    team
1609    2010    W01     1246
1610    2010    W02     1452
1611    2010    W03     1307
1612    2010    W04     1458
1613    2010    W05     1396

我需要采用以下格式的新数据框：

team  frequency
1246    01 
1452    02 
1307    03
1458    04
1396    05

频率值来自数据框seed中名为df的列中的值

W01 -> 01
W02 -> 02
W03 -> 03

我如何在熊猫中这样做？

Answer 1

下面的解决方案使用lambda函数应用正则表达式来删除非数字字符。

http://pythex.org/?regex=%5CD&test_string=L16a&ignorecase=0&multiline=0&dotall=0&verbose=0

import pandas as pd
import re

index=[1609,1610,1611,1612,1613,1700]
data = {'season':[2010,2010,2010,2010,2010,2010],
        'seed':['W01','W02','W03','W04','W05','L16a'],
        'team':[1246,1452,1307,1458,1396,0000]}

df = pd.DataFrame(data,index=index)

df['frequency'] = df['seed'].apply(lambda x: int(re.sub('\D', '', x)))
df2 = df[['team','frequency']].set_index('team')

Answer 2

# Setup your DataFrame
df = pd.DataFrame({'season': [2010]*5, 'seed': ['W0' + str(i) for i in range(1,6)], 'team': [1246, 1452, 1307, 1458, 1396]}, index=range(1609, 1614))
s = pd.Series(df['seed'].str[1:].values, index=df['team'], name='frequency')
print(s)

产量

team
1246    01
1452    02
1307    03
1458    04
1396    05
Name: frequency, dtype: object

在pandas数据帧中获取特定值

2 个答案: