replace nan in pandas
df['DataFrame Column'] = df['DataFrame Column'].fillna(0)replace nan in pandas
df['DataFrame Column'] = df['DataFrame Column'].fillna(0)pandas replace empty string with nan
df = df.replace(r'^s*$', np.NaN, regex=True)replace empty or nan excel date rows with custom date pandas python
>>> import collections
>>> Point = collections.namedtuple('Point', ['x', 'y'])
>>> p = Point(x=1.0, y=2.0)
>>> p
Point(x=1.0, y=2.0)
>>> p.x
1.0
>>> p.y
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