问题描述
您好我想通过删除丢失的信息来操纵数据，并将所有字母设为小写。但对于小写转换，我收到此警告：
Hi I would like to manipulate the data by removing missing information and make all letters lower case. But for the lowercase conversion, I get this warning:
E：\Program Files Extra \Python27 \lib\site-packages \ pandas \ core \frame.py:1808：UserWarning：Boolean系列键将重新编制索引以匹配DataFrame索引。
DataFrame index。，UserWarning）
C：\Users\KubiK\Desktop\FamSeach_NameHandling.py:18:SettingWithCopyWarning:
正在尝试设置一个值从DataFrame复制切片。
尝试使用.loc [row_indexer，col_indexer] = value而不是
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
请参阅文档中的警告：
frame3 [name] = frame3 [name]。str.lower（）
C：\ Users \ KubiK \Desktop \FamSeach_NameHandling .py：19：SettingWithCopyWarning：
尝试在DataFrame的切片副本上设置一个值。
尝试使用.loc [row_indexer，col_indexer] = value而不是
See the the caveats in the documentation: 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
请参阅文档中的警告：
frame3 [ethnicity] = frame3 [ethnicity]。str.lower（）
See the the caveats in the documentation: 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
此警告似乎不是致命的（至少对我的小样本数据而言），但我该如何处理呢？
This warning doesn't seem to be fatal (at least for my small sample data), but how should I deal with this?
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
推荐答案
当你设置frame2 / 3，尝试使用.loc，如下所示：
When you set frame2/3, trying using .loc as follows:
frame2 = frame.loc[~index_missEthnic, :]
frame3 = frame2.loc[~index_missName, :]
我认为这样可以解决你的错误'重新看到：
I think this would fix the error you're seeing:
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，但它没有回答您的问题：
You can also try the following, although it doesn't answer your question:
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，否则会保持值不变。
This converts any string in the column into lowercase, otherwise it leaves the value untouched.
这篇关于Python pandas数据框警告，建议使用.loc代替？的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！