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

Question

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]

Noob Coder · Accepted Answer · 2022-10-18 12:20:25Z

1

Try:

i_row = [-1, "NaN"]

df.iloc[0] = i_row
df

answered Oct 18, 2022 at 12:20

Noob Coder

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Comments

jezrael · Accepted Answer · 2022-10-18 12:53:09Z

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]

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