将 Pandas 系列作为列附加到 DataFrame
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Append Pandas Series to DataFrame as a column
提问by Amir
I have panadas dataframe (df) like ['key','col1','col2','col3'] and I have pandas series (sr) for which the index is the same as 'key' in data frame. I want to append the series to the dataframe at the new column called col4 with the same 'key'. I have the following code:
我有像 ['key','col1','col2','col3'] 这样的 panadas 数据框（df），并且我有 Pandas 系列（sr），其索引与数据框中的 'key' 相同。我想将该系列附加到名为 col4 的新列的数据框中，并使用相同的“键”。我有以下代码：
for index, row in segmention.iterrows():
df[df['key']==row['key']]['col4']=sr.loc[row['key']]
The code is very slow. I assume there should be more efficient and better way to do that. could you please help?
代码很慢。我认为应该有更有效和更好的方法来做到这一点。能否请你帮忙？
采纳答案by jezrael
Use mapas mentioned EdChum:
map如上所述使用EdChum：
df['col4'] = df['key'].map(sr)
print (df)
col1 col2 col3 key col4
0 4 7 1 A 2
1 5 8 3 B 4
2 6 9 5 C 1
Or assign with set_index:
或分配set_index：
df = df.set_index('key')
df['col4'] = sr
print (df)
col1 col2 col3 col4
key
A 4 7 1 2
B 5 8 3 4
C 6 9 5 1
If dont need aligndata in Seriesby keyuse (see difference 2,1,4vs 4,1,2):
如果不需要align在数据Series被key使用（见区别2,1,4VS 4,1,2）：
df['col4'] = sr.values
print (df)
col1 col2 col3 key col4
0 4 7 1 A 4
1 5 8 3 B 1
2 6 9 5 C 2
Sample:
样本：
df = pd.DataFrame({'key':[1,2,3],
'col1':[4,5,6],
'col2':[7,8,9],
'col3':[1,3,5]}, index=list('ABC'))
print (df)
col1 col2 col3 key
A 4 7 1 1
B 5 8 3 2
C 6 9 5 3
sr = pd.Series([4,1,2], index=list('BCA'))
print (sr)
B 4
C 1
A 2
dtype: int64
df['col4'] = df['key'].map(sr)
print (df)
col1 col2 col3 key col4
0 4 7 1 A 2
1 5 8 3 B 4
2 6 9 5 C 1
df = df.set_index('key')
df['col4'] = sr
print (df)
col1 col2 col3 col4
key
A 4 7 1 2
B 5 8 3 4
C 6 9 5 1
回答by Jan Zeiseweis
You can simply do:
你可以简单地做：
df['col4'] = sr
If don't misunderstand.
如果没有误会。
回答by Ted Petrou
This is really a good use case for join, where the left dataframe aligns a column with the index of the right dataframe/series. You have to make sure your Series has a name for it to work
这对于 来说确实是一个很好的用例join，其中左侧数据框将一列与右侧数据框/系列的索引对齐。你必须确保你的系列有一个名字才能工作
sr.name = 'some name'
df.join(sr, on='key')
