How to replace negative numbers in Pandas Data Frame by zero

Question

I would like to know if there is someway of replacing all DataFrame negative numbers by zeros?

Answer 1

If all your columns are numeric, you can use boolean indexing:

In [1]: import pandas as pd  In [2]: df = pd.DataFrame({'a': [0, -1, 2], 'b': [-3, 2, 1]})  In [3]: df Out[3]:     a  b 0  0 -3 1 -1  2 2  2  1  In [4]: df[df < 0] = 0  In [5]: df Out[5]:     a  b 0  0  0 1  0  2 2  2  1 

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For the more general case, this answer shows the private method _get_numeric_data:

In [1]: import pandas as pd  In [2]: df = pd.DataFrame({'a': [0, -1, 2], 'b': [-3, 2, 1],                            'c': ['foo', 'goo', 'bar']})  In [3]: df Out[3]:     a  b    c 0  0 -3  foo 1 -1  2  goo 2  2  1  bar  In [4]: num = df._get_numeric_data()  In [5]: num[num < 0] = 0  In [6]: df Out[6]:     a  b    c 0  0  0  foo 1  0  2  goo 2  2  1  bar 

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With timedelta type, boolean indexing seems to work on separate columns, but not on the whole dataframe. So you can do:

In [1]: import pandas as pd  In [2]: df = pd.DataFrame({'a': pd.to_timedelta([0, -1, 2], 'd'),    ...:                    'b': pd.to_timedelta([-3, 2, 1], 'd')})  In [3]: df Out[3]:          a       b 0  0 days -3 days 1 -1 days  2 days 2  2 days  1 days  In [4]: for k, v in df.iteritems():    ...:     v[v < 0] = 0    ...:       In [5]: df Out[5]:         a      b 0 0 days 0 days 1 0 days 2 days 2 2 days 1 days 

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Update: comparison with a pd.Timedelta works on the whole DataFrame:

In [1]: import pandas as pd  In [2]: df = pd.DataFrame({'a': pd.to_timedelta([0, -1, 2], 'd'),    ...:                    'b': pd.to_timedelta([-3, 2, 1], 'd')})  In [3]: df[df < pd.Timedelta(0)] = 0  In [4]: df Out[4]:         a      b 0 0 days 0 days 1 0 days 2 days 2 2 days 1 days