Question

在pandas数据帧中的

：我尝试的所有内容都替换了第一列中的键值对，但不是第一列和第二列中的值。这是代码：

module_names = {442990: 'Thank You', 442896:'Depression', 442924:'Irritability', 442879:'Anxiety', 442985:'sleep', 442875:'Meds'}
for key, value in module_names.iteritems():
    df['module'].replace(key,value,inplace=True)
print df.head(15)
for key, value in module_names.iteritems():
    df['inResponseTo'].replace(key,value,inplace=True)
print df.head(15)

输出：

        module inResponseTo botNickname  botID result  \
1      Thank You       442896   Web-Ducky  36931      4   
3     Depression       442924   Web-Ducky  36931      4   
5   Irritability       442879   Web-Ducky  36931      3   
7        Anxiety       442985   Web-Ducky  36931      4   
9          sleep       442875   Web-Ducky  36931    yes   
11          Meds       442875   Web-Ducky  36931    NaN   
13          Meds       442864   Web-Ducky  36931    NaN   
19     Thank You       442896       Ducky  36931      3

你可以看到我甚至都没有想要简洁，但我打破了它，看看我是否能发现我的错误。现在我很难过。 TIA

Answer 1

IIUC如果需要通过dict替换某些列中的值，则最简单的是删除循环：

df['inResponseTo'].replace(module_names,inplace=True)
print df
          module  inResponseTo botNickname  botID result
1      Thank You    Depression   Web-Ducky  36931      4
3     Depression  Irritability   Web-Ducky  36931      4
5   Irritability       Anxiety   Web-Ducky  36931      3
7        Anxiety         sleep   Web-Ducky  36931      4
9          sleep          Meds   Web-Ducky  36931    yes
11          Meds          Meds   Web-Ducky  36931    NaN
13          Meds        442864   Web-Ducky  36931    NaN
19     Thank You    Depression       Ducky  36931      3

如果需要map（其中不匹配get NaN）：

df['inResponseTo'] = df['inResponseTo'].map(module_names)
print (df)
          module  inResponseTo botNickname  botID result
1      Thank You    Depression   Web-Ducky  36931      4
3     Depression  Irritability   Web-Ducky  36931      4
5   Irritability       Anxiety   Web-Ducky  36931      3
7        Anxiety         sleep   Web-Ducky  36931      4
9          sleep          Meds   Web-Ducky  36931    yes
11          Meds          Meds   Web-Ducky  36931    NaN
13          Meds           NaN   Web-Ducky  36931    NaN
19     Thank You    Depression       Ducky  36931      3

编辑：

如果需要多列中的replace：

print (df)
          module  inResponseTo botNickname  botID  result
1      Thank You        442896   Web-Ducky  36931  442896
3     Depression        442924   Web-Ducky  36931  442924
5   Irritability        442879   Web-Ducky  36931  442879
7        Anxiety        442985   Web-Ducky  36931  442985
9          sleep        442875   Web-Ducky  36931  442875
11          Meds        442875   Web-Ducky  36931  442875
13          Meds        442864   Web-Ducky  36931  442864
19     Thank You        442896       Ducky  36931  442896

df[['inResponseTo','result']] = df[['inResponseTo','result']].replace(module_names)
print (df)
          module  inResponseTo botNickname  botID        result
1      Thank You    Depression   Web-Ducky  36931    Depression
3     Depression  Irritability   Web-Ducky  36931  Irritability
5   Irritability       Anxiety   Web-Ducky  36931       Anxiety
7        Anxiety         sleep   Web-Ducky  36931         sleep
9          sleep          Meds   Web-Ducky  36931          Meds
11          Meds          Meds   Web-Ducky  36931          Meds
13          Meds        442864   Web-Ducky  36931        442864
19     Thank You    Depression       Ducky  36931    Depression

Python 2.7替换pandas DF中的所有值

1 个答案: