How to insert multiple rows in a dataframe in python without changing the Index?-CodePudding

I have a dataframe , How can i insert a row with Twith multiple values such that the index always starts with 0.

df:

   Topics_numberrs_k    Topics_assignment_k
0   0                   Int64Index([ 175, 920, 1016, 2068, 2162, 3385]
1   1                   Int64Index([ 2, 5, 6, 7, 8, 9]

Expected output:

    Topics_numberrs_k   Topics_assignment_k
0   -1                  NaN
1    0                  Int64Index([ 175, 920, 1016, 2068, 2162, 3385]
2    1                  Int64Index([ 2, 5, 6, 7, 8, 9]

CodePudding user response：

Try:

i_row = [-1, "NaN"]

df.iloc[0] = i_row
df

CodePudding user response：

Use concat with new DataFrame and append existing:

df = pd.concat([pd.DataFrame([[-1, np.nan]], columns=df.columns), df], ignore_index=True)
print (df)
   Topics_numberrs_k                             Topics_assignment_k
0                 -1                                             NaN
1                  0  Int64Index([ 175, 920, 1016, 2068, 2162, 3385]
2                  1                  Int64Index([ 2, 5, 6, 7, 8, 9]

Or create new row and sorting index by DataFrame.sort_index, if necessary convert Topics_numberrs_k to integers:

df.loc[-1] = [-1, np.nan]

df = df.sort_index(ignore_index=True).astype({'Topics_numberrs_k':'int'})
print (df)
   Topics_numberrs_k                             Topics_assignment_k
0                 -1                                             NaN
1                  0  Int64Index([ 175, 920, 1016, 2068, 2162, 3385]
2                  1                  Int64Index([ 2, 5, 6, 7, 8, 9]