Convert pandas Series to DataFrame

问题

I have a Pandas series sf:

email
email1@email.com    [1.0, 0.0, 0.0]
email2@email.com    [2.0, 0.0, 0.0]
email3@email.com    [1.0, 0.0, 0.0]
email4@email.com    [4.0, 0.0, 0.0]
email5@email.com    [1.0, 0.0, 3.0]
email6@email.com    [1.0, 5.0, 0.0]

And I would like to transform it to the following DataFrame:

index | email             | list
_____________________________________________
0     | email1@email.com  | [1.0, 0.0, 0.0]
1     | email2@email.com  | [2.0, 0.0, 0.0]
2     | email3@email.com  | [1.0, 0.0, 0.0]
3     | email4@email.com  | [4.0, 0.0, 0.0]
4     | email5@email.com  | [1.0, 0.0, 3.0]
5     | email6@email.com  | [1.0, 5.0, 0.0]

I found a way to do it, but I doubt it\'s the more efficient one:

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)

回答1:

Rather than create 2 temporary dfs you can just pass these as params within a dict using the DataFrame constructor:

pd.DataFrame({'email':sf.index, 'list':sf.values})

There are lots of ways to construct a df, see the docs

回答2:

to_frame():

Starting with the following Series, df:

email
email1@email.com    A
email2@email.com    B
email3@email.com    C
dtype: int64

I use to_frame to convert the series to DataFrame:

df = df.to_frame().reset_index()

    email               0
0   email1@email.com    A
1   email2@email.com    B
2   email3@email.com    C
3   email4@email.com    D

Now all you need is to rename the column name and name the index column:

df = df.rename(columns= {0: 'list'})
df.index.name = 'index'

Your DataFrame is ready for further analysis.

Update: I just came across this link where the answers are surprisingly similar to mine here.

回答3:

One line answer would be

myseries.to_frame(name='my_column_name')
myseries.reset_index(drop=True, inplace=True)  # As needed

回答4:

Series.reset_index with `name` argument

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_index will result in something like,

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 name parameter.

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

If you want to create a DataFrame without promoting the index to a column, use Series.to_frame, as suggested in this answer. This also supports a name parameter.

s.to_frame(name='B')

   B
A   
a  1
b  2
c  3

pd.DataFrame Constructor

You can also do the same thing as Series.to_frame by specifying a columns param:

pd.DataFrame(s, columns=['B'])

   B
A   
a  1
b  2
c  3

回答5:

Why not series_obj.to_frame()? It gets my job done.

来源：https://stackoverflow.com/questions/26097916/convert-pandas-series-to-dataframe

标签

python

pandas

dataframe

series