Is there any way to specify the index that I want for a new row, when appending the row to a dataframe?
The original documentation provides the following example:
In [1301]: df = DataFrame(np.random.randn(8, 4), columns=['A','B','C','D'])
In [1302]: df
Out[1302]:
A B C D
0 -1.137707 -0.891060 -0.693921 1.613616
1 0.464000 0.227371 -0.496922 0.306389
2 -2.290613 -1.134623 -1.561819 -0.260838
3 0.281957 1.523962 -0.902937 0.068159
4 -0.057873 -0.368204 -1.144073 0.861209
5 0.800193 0.782098 -1.069094 -1.099248
6 0.255269 0.009750 0.661084 0.379319
7 -0.008434 1.952541 -1.056652 0.533946
In [1303]: s = df.xs(3)
In [1304]: df.append(s, ignore_index=True)
Out[1304]:
A B C D
0 -1.137707 -0.891060 -0.693921 1.613616
1 0.464000 0.227371 -0.496922 0.306389
2 -2.290613 -1.134623 -1.561819 -0.260838
3 0.281957 1.523962 -0.902937 0.068159
4 -0.057873 -0.368204 -1.144073 0.861209
5 0.800193 0.782098 -1.069094 -1.099248
6 0.255269 0.009750 0.661084 0.379319
7 -0.008434 1.952541 -1.056652 0.533946
8 0.281957 1.523962 -0.902937 0.068159
where the new row gets the index label automatically. Is there any way to control the new label?
See Question&Answers more detail:
os 与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…