I am facing an error when we have a column which has datatype as a string and the value like col1 col2 1 .89
So, when I am using:
def azureml_main(dataframe1 = None, dataframe2 = None):
# Execution logic goes here
print('Input pandas.DataFrame #1:')
import pandas as pd
import numpy as np
from sklearn.kernel_approximation import RBFSampler
x =dataframe1.iloc[:,2:1080]
print x
df1 = dataframe1[['colname']]
change = np.array(df1)
b = change.ravel()
print b
rbf_feature = RBFSampler(gamma=1, n_components=100,random_state=1)
print rbf_feature
print "test"
X_features = rbf_feature.fit_transform(x)
After this, I am getting an error as can't convert non-int into type float