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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?

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