Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
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IndexError: list index out of range if type(df[depVar])==int32 #69
if the type of target columns is int32,it seems meet some mistake ,because the function classify_print_vars does not treat type(int32). if I define target columns astype int64, the problem will solve.
please add the infer function to type int32. Thanks!
if type(depVar) == str:
if depVar == '':
cols_list = list(dft)
problem_type = 'Clustering'
classes = []
else:
try:
problem_type = analyze_problem_type(dft, depVar,verbose)
except:
print('Could not find given target var in data set. Please check input')
### return the data frame as is ############
return dfte
cols_list = list_difference(list(dft),depVar)
if dft[depVar].dtype == object:
classes = dft[depVar].factorize()[1].tolist()
#### You dont have to convert it since most charts can take string vars as target ####
#dft[depVar] = dft[depVar].factorize()[0]
elif dft[depVar].dtype == np.int64: ###################here#################
classes = dft[depVar].factorize()[1].tolist()
elif dft[depVar].dtype == bool:
dft[depVar] = dft[depVar].astype(int)
classes = dft[depVar].unique().astype(int).tolist()
elif dft[depVar].dtype == float and problem_type.endswith('Classification'):
classes = dft[depVar].factorize()[1].tolist()
else:
classes = []
if the type of target columns is int32,it seems meet some mistake ,because the function classify_print_vars does not treat type(int32). if I define target columns astype int64, the problem will solve. please add the infer function to type int32. Thanks!