Replicating rows based on index multiplies the rows instead of replicating

Question

I have dataframe, where i would like to replicate few rows:

         X      Y       diff        No
Index                              
1d       0.000   0.017  0.000e+00   0
2D       0.083   0.017  3.000e-03   1
3D       0.250   0.017  7.200e-03   2
6D       0.500   0.019  2.400e-03   3
1DD      1.000   0.020  2.400e-03   4
2DD      2.000   0.023  1.300e-03   5
3DD      3.000   0.024  1.000e-03   6
5DD      5.000   0.026  6.500e-04   7
7DD      7.000   0.027  2.667e-04   8
10DD     10.000  0.028  1.200e-04   9
20DD     20.000  0.029  1.200e-04   10
30DD     30.000  0.031  0.000e+00   11

I want to replicate 30DD 30 times and 20DD 20 times and 10DD 10 times with same index name.

I tried this, instead of replicating it multiplies

for i in range(4):
    test1 = df.append(df.ix['30DD']*30)

      X      Y       diff        No
Index                              
1d       0.000   0.017  0.000e+00   0
2D       0.083   0.017  3.000e-03   1
3D       0.250   0.017  7.200e-03   2
6D       0.500   0.019  2.400e-03   3
1DD      1.000   0.020  2.400e-03   4
2DD      2.000   0.023  1.300e-03   5
3DD      3.000   0.024  1.000e-03   6
5DD      5.000   0.026  6.500e-04   7
7DD      7.000   0.027  2.667e-04   8
10DD     10.000  0.028  1.200e-04   9
20DD     20.000  0.029  1.200e-04   10
30DD     30.000  0.031  0.000e+00   11
30DD     900     0.918  0           330

Side note: `ix` has now been deprecated. Use `loc` or `iloc` instead. — jpp, Jun 24 '18 at 13:58

jezrael · Accepted Answer · 2018-06-24T14:10:37.270

1

Add new rows, but subtract 1, because append to original DataFrame:

vals = ['30DD'] * 29 + ['20DD'] * 19 + ['10DD'] * 9
df = df.append(df.loc[vals])

Last if want sorting values by numbers of index values:

df = df.iloc[df.index.str.extract('(\d+)').astype(int).squeeze().argsort()]

edited Jun 24 '18 at 14:10

answered Jun 24 '18 at 13:53

jezrael

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1

Yes . I wanted 9 rows , 19 rows and 9 rows to be added as I have already one. This is correct – Magg_rs Jun 24 '18 at 14:05

score 0 · Answer 2 · answered Jun 24 '18 at 13:58

0

Using numpy.repeat, you can create a list of indices for rows you wish to append. Then feed to pd.DataFrame.loc and append to your original dataframe.

vals = ['30DD', '20DD', '10DD']
counts = [30, 20, 10]

df = df.append(df.loc[np.repeat(vals, counts)])

answered Jun 24 '18 at 13:58

jpp

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Not clear to me. But, more importantly, I think OP can figure out how to subtract one. – jpp Jun 24 '18 at 14:01
be free correct it, or there is some problem with it? – jezrael Jun 24 '18 at 14:09

Replicating rows based on index multiplies the rows instead of replicating

2 Answers2