How to convert pandas Series to DataFrame-CodePudding

I have a pandas Series as se:

wind      yes
humidity     high
weather    sunny
temp    hot
conclusion    bad
Name: 1, dtype: object

And I want to convert it into a dataframe like:

  | weather| temp | humidity | wind | conclusion
0 | sunny | hot  | high | yes | bad

I've tried

pd.DataFrame(se)

but it turns out to be something else

wind      yes
humidity     high
weather    sunny
temp    hot
conclusion    bad

CodePudding user response：

Use to_frame and transpose your new dataframe:

df = sr.to_frame(0).T
print(df)

# Output:
  wind humidity weather temp conclusion
0  yes     high   sunny  hot        bad

Setup

data = {'wind': 'yes',
        'humidity': 'high',
        'weather': 'sunny',
        'temp': 'hot',
        'conclusion': 'bad'}
sr = pd.Series(data, name=1)
print(sr)

# Output
wind            yes
humidity       high
weather       sunny
temp            hot
conclusion      bad
Name: 1, dtype: object

CodePudding user response：

Use this, it might help :)

   se.to_frame()

CodePudding user response：

More than likely you got this series buy selecting a single row of your originaldataframe using .loc[0] or .iloc[0]. Try using double brackets to select a single row from a dataframe as a dataframe instead of converting to a series.

df.iloc[[0]]

df.loc[[0]]

MVCE:

df = pd.DataFrame({'Col1':[*'ABC'], 
              'Col2':'Alpha Bravo Charlie'.split(' '),
              'Col3': [1,2,3]})

df.loc[0]

Outputs a pd.Series:

Col1        A
Col2    Alpha
Col3        1
Name: 0, dtype: object

Now try double brackets:

df.loc[[0]]

Outputs a signle row pd.Dataframe:

  Col1   Col2  Col3
0    A  Alpha     1

And, likewise with .iloc.