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- df = pd.DataFrame({'b':[False,True,False,True,False]})
- # changes all False values to NaN
- df.loc[~df['b'], 'b'] = np.nan
- print(df.to_dict())
- # {'b': {0: nan, 1: 1.0, 2: nan, 3: 1.0, 4: nan}}
- In[200]:
- df = pd.DataFrame({'b':[False,True,False,True,False]})
- df['b'] = df['b'].astype(np.object)
- # changes all False values to NaN
- df.loc[df['b']==False, 'b'] = np.nan
- df
- Out[200]:
- b
- 0 NaN
- 1 True
- 2 NaN
- 3 True
- 4 NaN
- KeyError: '[-1 -2 -1 -2 -1] not in index'
- print(type(df['b'].iloc[0]))
- print(type(df['b'].iloc[1]))
- <class 'float'>
- <class 'bool'>
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