Windows issue: cannot astype a datetimelike from [datetime64[ns]] to [int32]
Here is the relevant code to the error:
class TimeToEpoch(BaseEstimator, TransformerMixin):
"""Convert a datetime column into seconds-since-epoch"""
def __init__(self, col):
self.col = col
def fit(self, X, y=None):
return self
def transform(self, X, y=None):
return X[self.col].astype(int).to_frame(self.col)
features = [
('budget', Take('budget')),
('gross', Take('gross')),
('votes', Take('votes')),
('year', Take('year')),
('genre', OHE('genre')),
('rating', OHE('rating')),
('time', TimeToEpoch('released'))
]
pipe = Pipeline([
('feat', FeatureUnion(features)),
('scale', StandardScaler())
])
trans = pipe.fit_transform(df)
Basically, this piece of code is trying to convert the movie dates into seconds (which includes "#####", or NaN).
While this piece of code works on a user's Mac, this doesn't work on mine, which is a PC. Can someone figure out the problem relating to Windows?
windows pandas pipeline
asked Nov 24 '18 at 3:00
AndreAndre
62
add a comment |
Here is the relevant code to the error:
class TimeToEpoch(BaseEstimator, TransformerMixin):
"""Convert a datetime column into seconds-since-epoch"""
def __init__(self, col):
self.col = col
def fit(self, X, y=None):
return self
def transform(self, X, y=None):
return X[self.col].astype(int).to_frame(self.col)
features = [
('budget', Take('budget')),
('gross', Take('gross')),
('votes', Take('votes')),
('year', Take('year')),
('genre', OHE('genre')),
('rating', OHE('rating')),
('time', TimeToEpoch('released'))
]
pipe = Pipeline([
('feat', FeatureUnion(features)),
('scale', StandardScaler())
])
trans = pipe.fit_transform(df)
Basically, this piece of code is trying to convert the movie dates into seconds (which includes "#####", or NaN).
While this piece of code works on a user's Mac, this doesn't work on mine, which is a PC. Can someone figure out the problem relating to Windows?
windows pandas pipeline
asked Nov 24 '18 at 3:00
AndreAndre
62
add a comment |
Here is the relevant code to the error:
class TimeToEpoch(BaseEstimator, TransformerMixin):
"""Convert a datetime column into seconds-since-epoch"""
def __init__(self, col):
self.col = col
def fit(self, X, y=None):
return self
def transform(self, X, y=None):
return X[self.col].astype(int).to_frame(self.col)
features = [
('budget', Take('budget')),
('gross', Take('gross')),
('votes', Take('votes')),
('year', Take('year')),
('genre', OHE('genre')),
('rating', OHE('rating')),
('time', TimeToEpoch('released'))
]
pipe = Pipeline([
('feat', FeatureUnion(features)),
('scale', StandardScaler())
])
trans = pipe.fit_transform(df)
Basically, this piece of code is trying to convert the movie dates into seconds (which includes "#####", or NaN).
While this piece of code works on a user's Mac, this doesn't work on mine, which is a PC. Can someone figure out the problem relating to Windows?
windows pandas pipeline
asked Nov 24 '18 at 3:00
AndreAndre
62
Here is the relevant code to the error:
class TimeToEpoch(BaseEstimator, TransformerMixin):
"""Convert a datetime column into seconds-since-epoch"""
def __init__(self, col):
self.col = col
def fit(self, X, y=None):
return self
def transform(self, X, y=None):
return X[self.col].astype(int).to_frame(self.col)
features = [
('budget', Take('budget')),
('gross', Take('gross')),
('votes', Take('votes')),
('year', Take('year')),
('genre', OHE('genre')),
('rating', OHE('rating')),
('time', TimeToEpoch('released'))
]
pipe = Pipeline([
('feat', FeatureUnion(features)),
('scale', StandardScaler())
])
trans = pipe.fit_transform(df)
Basically, this piece of code is trying to convert the movie dates into seconds (which includes "#####", or NaN).
While this piece of code works on a user's Mac, this doesn't work on mine, which is a PC. Can someone figure out the problem relating to Windows?
windows pandas pipeline
windows pandas pipeline
asked Nov 24 '18 at 3:00
AndreAndre
62
asked Nov 24 '18 at 3:00
AndreAndre
62
asked Nov 24 '18 at 3:00
AndreAndre
62
asked Nov 24 '18 at 3:00
AndreAndre
62
asked Nov 24 '18 at 3:00
AndreAndre
62
62
add a comment |
add a comment |
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