[ Why does this return 'Too Many Indexers'? ]
My code is:
import pandas as pd import numpy as np from sklearn import svm name = '../CLIWOC/CLIWOC15.csv' data = pd.read_csv(name) # Get info into dataframe and drop NaNs data = pd.concat([data.UTC, data.Lon3, data.Lat3, data.Rain]).dropna(how='any') # Set target X = data.loc[:, ['UTC', 'Lon3', 'Lat3']] y = data['Rain'] # Partition a test set Xtest = X[-1] ytest = y[-1] X = X[1:-2] y = y[1:-2] # Train classifier classifier = svm.svc(gamma=0.01, C=100.) classifier.fit(X, y) classifier.predict(Xtest) y
Arriving at the 'set target' section, the compiler returns the error 'Too Many Indexers'. I lifted this syntax directly from the documentation, so I'm unsure what could be wrong. The csv is organized with these headers for columns of data.
Without your data, it is hard to verify. My immediate suspicion, however, is that you need to pass a numpy array instead of a DataFrame.
Try this to extract them:
# Set target X = data.loc[:, ['UTC', 'Lon3', 'Lat3']].values y = data['Rain'].values