Python 将 Pandas 系列转换为 DataFrame
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Convert pandas Series to DataFrame
提问by woshitom
I have a Pandas series sf:
我有一个熊猫系列科幻小说：
email
[email protected] [1.0, 0.0, 0.0]
[email protected] [2.0, 0.0, 0.0]
[email protected] [1.0, 0.0, 0.0]
[email protected] [4.0, 0.0, 0.0]
[email protected] [1.0, 0.0, 3.0]
[email protected] [1.0, 5.0, 0.0]
And I would like to transform it to the following DataFrame:
我想将其转换为以下 DataFrame：
index | email | list
_____________________________________________
0 | [email protected] | [1.0, 0.0, 0.0]
1 | [email protected] | [2.0, 0.0, 0.0]
2 | [email protected] | [1.0, 0.0, 0.0]
3 | [email protected] | [4.0, 0.0, 0.0]
4 | [email protected] | [1.0, 0.0, 3.0]
5 | [email protected] | [1.0, 5.0, 0.0]
I found a way to do it, but I doubt it's the more efficient one:
我找到了一种方法，但我怀疑它是更有效的方法：
df1 = pd.DataFrame(data=sf.index, columns=['email'])
df2 = pd.DataFrame(data=sf.values, columns=['list'])
df = pd.merge(df1, df2, left_index=True, right_index=True)
采纳答案by EdChum
回答by Shoresh
to_frame():
to_frame():
Starting with the following Series, df:
从以下系列开始，df：
email
[email protected] A
[email protected] B
[email protected] C
dtype: int64
I use to_frameto convert the series to DataFrame:
我使用to_frame将系列转换为 DataFrame：
df = df.to_frame().reset_index()
email 0
0 [email protected] A
1 [email protected] B
2 [email protected] C
3 [email protected] D
Now all you need is to rename the column name and name the index column:
现在您只需要重命名列名并命名索引列：
df = df.rename(columns= {0: 'list'})
df.index.name = 'index'
Your DataFrame is ready for further analysis.
您的 DataFrame 已准备好进行进一步分析。
Update: I just came across this linkwhere the answers are surprisingly similar to mine here.
更新：我刚刚看到这个链接，这里的答案与我的惊人相似。
回答by Mysterious
One line answer would be
一行答案是
myseries.to_frame(name='my_column_name')
myseries.reset_index(drop=True, inplace=True) # As needed
回答by cs95
Series.reset_indexwith nameargument
Series.reset_index有name论据
Often the use case comes up where a Series needs to be promoted to a DataFrame. But if the Series has no name, then reset_indexwill result in something like,
通常会出现需要将 Series 提升为 DataFrame 的用例。但是如果系列没有名字，那么reset_index会导致类似的结果，
s = pd.Series([1, 2, 3], index=['a', 'b', 'c']).rename_axis('A')
s
A
a 1
b 2
c 3
dtype: int64
s.reset_index()
A 0
0 a 1
1 b 2
2 c 3
Where you see the column name is "0". We can fix this be specifying a nameparameter.
您看到的列名是“0”。我们可以通过指定一个name参数来解决这个问题。
s.reset_index(name='B')
A B
0 a 1
1 b 2
2 c 3
s.reset_index(name='list')
A list
0 a 1
1 b 2
2 c 3
Series.to_frame
Series.to_frame
If you want to create a DataFrame without promoting the index to a column, use Series.to_frame, as suggested in this answer. This alsosupports a name parameter.
如果您想在不将索引提升到列的情况下创建 DataFrame，请使用Series.to_frame，如本答案中建议的那样。这也支持名称参数。
s.to_frame(name='B')
B
A
a 1
b 2
c 3
pd.DataFrameConstructor
pd.DataFrame构造函数
You can also do the same thing as Series.to_frameby specifying a columnsparam:
你也可以Series.to_frame通过指定columns参数来做同样的事情：
pd.DataFrame(s, columns=['B'])
B
A
a 1
b 2
c 3
回答by Giorgos Myrianthous
Series.to_framecan be used to convert a Seriesto DataFrame.
Series.to_frame可用于将 a 转换Series为DataFrame.
# The provided name (columnName) will substitute the series name
df = series.to_frame('columnName')
For example,
例如，
s = pd.Series(["a", "b", "c"], name="vals")
df = s.to_frame('newCol')
print(df)
newCol
0 a
1 b
2 c
