I have the following dataframne:
df
Name Jan Feb Mar
Description
New A 34 32 54
Old B 65 98 05
Retired C 96 26 43
Description is an index column.
I am trying to assign a value to variable as follows:
variable = df[(df['Description']=='Retired') & (df['Name']=='C')]["Jan"]
But i am getting an error:
ValueError: setting an array element with a sequence.
Is there a way to do it?
Use DataFrame.loc with compare index - output is Series - with one or more values:
variable = df.loc[(df.index=='Retired') & (df['Name']=='C'), "Jan"]
print (variable)
Description
Retired 96
Name: Jan, dtype: int64
If need select first and always exist at least one value use:
print (variable.iat[0])
96
But if possible no match, then is returned empty Series and cannot select like above, then is possible use next-iter trick with possible set default value if empty Series:
variable = df.loc[(df.index=='Retired') & (df['Name']=='another'), "Jan"]
print (variable)
Series([], Name: Jan, dtype: int64)
print (next(iter(variable), 'no match'))
no match
Another better solution is add Name to index for MultiIndex and then select by tuple if need scalar output:
df = df.set_index('Name', append=True)
variable = df.loc[('Retired','C'), "Jan"]
print (variable)
96
no_days = df.loc[df.index,'Name'].at['Jan'] . I am not able to use this since i have to filter the description column also.
df = df.set_index('Name', append=True) variable = df.loc[('Retired','C'), "Jan"] print (variable) is not possible use?Description Name Retired C 96 Name: Jan, dtype: float64