I use the following code to drop some rows based on their position in df:
for i in irange:
df.drop(df.iloc[i].name, inplace=True)
However, it seems I can't do it in a loop and I get:
raise IndexError("single positional indexer is out-of-bounds")
IndexError: single positional indexer is out-of-bounds
This other question is about columns, while mine is about rows:
If you want to drop indices from a list of positions, you should use:
df = pd.DataFrame({'col': 1}, index=list('abcdef'))
irange = [1, 4, 5]
df.drop(df.index[irange], inplace=True)
Note however that this requires unique indices, if not:
df = pd.DataFrame({'col': 1}, index=list('abcdef'))
irange = [1, 4, 5]
out = df.loc[np.isin(np.arange(len(df)), irange)]
Output:
col
b 1
e 1
f 1
irange?