I have a dataframe:
df =
col1 col2
0 [0.1,0.2,0.3] [1,2,3]
1 [0.5,0.6,0.7] [11,12,13]
My goal: to re-create data frame from index 0:
new_df =
new_col1 new_col2
0 0.1 1
1 0.2 2
2 0.3 3
What I tried was trying to access row by row:
new_col1 = df.col1[0]
new_col2 = df.col2[0]
But new_col1 results in below instead of a list. So I am unsure how to approach this.
0 [0.1,0.2,0.3]
Name: col1, dtype: object
Thanks.
Here is a way by using apply.
df.apply(pd.Series.explode).loc[0]
You can create new DataFrame by select first row by DataFrame.loc or DataFrame.iloc and then transpose by DataFrame.T with DataFrame.add_prefix for new columns names:
df1 = pd.DataFrame(df.iloc[0].tolist(), index=df.columns).T.add_prefix('new_')
print (df1)
new_col1 new_col2
0 0.1 1.0
1 0.2 2.0
2 0.3 3.0
new_df = pd.DataFrame([new_col1, new_col2]).transpose()
If you want to add column names,
new_df.columns = ["new_col1","new_col2"]
you can use the list() function for this
>>> new_col1
[0.1, 0.2, 0.3]
>>> new_col1_=list(new_col1)
[0.1, 0.2, 0.3]
>>> type(new_col1_)
<class 'list'>
