Creating new column based on values of other column (condition on date present in multiple columns) in Python
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In the dataset, there are several columns with date as value. I need to create new columns based on certain condition on the date values. Certain date values are replaced by "N" character, so it appears that entire column is being treated as string.
Date 1 Date 2
2012-12-03 2012-12-07
2004-12-31 N
N 2010-10-20
2014-11-22 N
2014-12-16 2014-12-31
df = read_csv('filepath')
df['Level'] = np.where(df['Date 1'] - df['Date 2'] > '60', 'Level 1','Level 2')
This is giving me an error
TypeError: unsupported operand type(s) for -: 'str' and 'str'
Also the condition will include another scenario (the syntax may not be correct)
np.where(df['Date 1'] == pd.datetime('YYYY-MM-DD') & df['Date 1'] == "N", 'Level 1','Level 2')
Any direction in this regard would be helpful.
python-3.x date condition multiple-columns
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up vote
0
down vote
favorite
In the dataset, there are several columns with date as value. I need to create new columns based on certain condition on the date values. Certain date values are replaced by "N" character, so it appears that entire column is being treated as string.
Date 1 Date 2
2012-12-03 2012-12-07
2004-12-31 N
N 2010-10-20
2014-11-22 N
2014-12-16 2014-12-31
df = read_csv('filepath')
df['Level'] = np.where(df['Date 1'] - df['Date 2'] > '60', 'Level 1','Level 2')
This is giving me an error
TypeError: unsupported operand type(s) for -: 'str' and 'str'
Also the condition will include another scenario (the syntax may not be correct)
np.where(df['Date 1'] == pd.datetime('YYYY-MM-DD') & df['Date 1'] == "N", 'Level 1','Level 2')
Any direction in this regard would be helpful.
python-3.x date condition multiple-columns
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
In the dataset, there are several columns with date as value. I need to create new columns based on certain condition on the date values. Certain date values are replaced by "N" character, so it appears that entire column is being treated as string.
Date 1 Date 2
2012-12-03 2012-12-07
2004-12-31 N
N 2010-10-20
2014-11-22 N
2014-12-16 2014-12-31
df = read_csv('filepath')
df['Level'] = np.where(df['Date 1'] - df['Date 2'] > '60', 'Level 1','Level 2')
This is giving me an error
TypeError: unsupported operand type(s) for -: 'str' and 'str'
Also the condition will include another scenario (the syntax may not be correct)
np.where(df['Date 1'] == pd.datetime('YYYY-MM-DD') & df['Date 1'] == "N", 'Level 1','Level 2')
Any direction in this regard would be helpful.
python-3.x date condition multiple-columns
In the dataset, there are several columns with date as value. I need to create new columns based on certain condition on the date values. Certain date values are replaced by "N" character, so it appears that entire column is being treated as string.
Date 1 Date 2
2012-12-03 2012-12-07
2004-12-31 N
N 2010-10-20
2014-11-22 N
2014-12-16 2014-12-31
df = read_csv('filepath')
df['Level'] = np.where(df['Date 1'] - df['Date 2'] > '60', 'Level 1','Level 2')
This is giving me an error
TypeError: unsupported operand type(s) for -: 'str' and 'str'
Also the condition will include another scenario (the syntax may not be correct)
np.where(df['Date 1'] == pd.datetime('YYYY-MM-DD') & df['Date 1'] == "N", 'Level 1','Level 2')
Any direction in this regard would be helpful.
python-3.x date condition multiple-columns
python-3.x date condition multiple-columns
asked 2 days ago
Devarshi Mandal
13
13
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