Python pandas slice dataframe by multiple index ranges
You can use numpy's r_
"slicing trick":
df = pd.DataFrame({'a':range(10,100)})
df.iloc[pd.np.r_[10:12, 25:28]]
NOTE: this now gives a warning The pandas.np module is deprecated and will be removed from pandas in a future version. Import numpy directly instead
. To do that, you can import numpy as np
and then slice the following way:
df.iloc[np.r_[10:12, 25:28]]
This gives:
a
10 20
11 21
25 35
26 36
27 37
You can take advantage of pandas isin function.
df = pd.DataFrame({'a':range(10,100)})
ls = [i for i in range(10,12)] + [i for i in range(25,28)]
df[df.index.isin(ls)]
a
10 20
11 21
25 35
26 36
27 37