Python pandas 数据框警告，建议改用 .loc 吗？

Question

您好，我想通过删除缺失的信息并将所有字母小写来操作数据。但对于小写转换，我收到以下警告：

E:\Program Files Extra\Python27\lib\site-packages\pandas\core\frame.py:1808: UserWarning: Boolean Series key will be reindexed to match DataFrame index.
  "DataFrame index.", UserWarning)
C:\Users\KubiK\Desktop\FamSeach_NameHandling.py:18: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

请参阅文档中的注意事项：http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy frame3["name"] = frame3["name"].str.lower()

C:\Users\KubiK\Desktop\FamSeach_NameHandling.py:19: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

请参阅文档中的注意事项：http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy frame3["ethnicity"] = frame3["ethnicity"].str.lower()

import pandas as pd
from pandas import DataFrame

# Get csv file into data frame
data = pd.read_csv("C:\Users\KubiK\Desktop\OddNames_sampleData.csv")
frame = DataFrame(data)
frame.columns = ["name", "ethnicity"]
name = frame.name
ethnicity = frame.ethnicity

# Remove missing ethnicity data cases
index_missEthnic = frame.ethnicity.isnull()
index_missName = frame.name.isnull()
frame2 = frame[index_missEthnic != True]
frame3 = frame2[index_missName != True]

# Make all letters into lowercase
frame3["name"] = frame3["name"].str.lower()
frame3["ethnicity"] = frame3["ethnicity"].str.lower()

# Test outputs
print frame3

这个警告似乎并不致命（至少对于我的小样本数据而言），但我应该如何处理呢？

样本数据

Name    Ethnicity
Thos C. Martin                              Russian
Charlotte Wing                              English
Frederick A T Byrne                         Canadian
J George Christe                            French
Mary R O'brien                              English
Marie A Savoie-dit Dugas                    English
J-b'te Letourneau                           Scotish
Jane Mc-earthar                             French
Amabil?? Bonneau                            English
Emma Lef??c                                 French
C., Akeefe                                  African
D, James Matheson                           English
Marie An: Thomas                            English
Susan Rrumb;u                               English
                                            English
Kaio Chan   

Answer 1

当你设置 frame2/3 时，尝试使用 .loc 如下：

frame2 = frame.loc[~index_missEthnic, :]
frame3 = frame2.loc[~index_missName, :]

我认为这可以解决您看到的错误：

frame3.loc[:, "name"] = frame3.loc[:, "name"].str.lower()
frame3.loc[:, "ethnicity"] = frame3.loc[:, "ethnicity"].str.lower()

您也可以尝试以下方法，尽管它不能回答您的问题：

frame3.loc[:, "name"] = [t.lower() if isinstance(t, str) else t for t in frame3.name]
frame3.loc[:, "ethnicity"] = [t.lower() if isinstance(t, str) else t for t in frame3. ethnicity]

这会将列中的任何字符串转换为小写，否则它会保持该值不变。

Answer 2

不知道为什么需要这么多布尔值... 另请注意，.isnull() 不会捕获空字符串。 在应用.lower() 之前过滤空字符串似乎也没有必要。 但这是有必要的......这对我有用：

frame = pd.DataFrame({'name':['Abc Def', 'EFG GH', ''], 'ethnicity':['Ethnicity1','', 'Ethnicity2']})
print frame

    ethnicity     name
0  Ethnicity1  Abc Def
1               EFG GH
2  Ethnicity2         

name_null = frame.name.str.len() == 0
frame.loc[~name_null, 'name'] = frame.loc[~name_null, 'name'].str.lower()
print frame

    ethnicity     name
0  Ethnicity1  abc def
1               efg gh
2  Ethnicity2