In [1]: import pandas as pd
In [2]: df = pd.DataFrame([
...: [1, 2, 'a', 3],
...: [4, 5, 'b', 6],
...: [7, 8, 'c', 9],
...: ])
In [3]: df
Out[3]:
0 1 2 3
0 1 2 a 3
1 4 5 b 6
2 7 8 c 9
In [4]: df.dtypes
Out[4]:
0 int64
1 int64
2 object
3 int64
dtype: object
In [5]: df[df.columns[df.dtypes != object]]
Out[5]:
0 1 3
0 1 2 3
1 4 5 6
2 7 8 9
In [6]:
If it won't be simple, it simply won't be. [Hire me, source code] by Miki Tebeka, CEO, 353Solutions
Tuesday, February 23, 2016
Removing String Columns from a DataFrame
Sometimes you want to work just with numerical columns in a pandas DataFrame. The rule of thumb is that everything that has a type of object is something not numeric (you can get fancier with numpy.issubdtype). We're going to use the DataFrame dtypes with some boolean indexing to accomplish this.
Labels:
python
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