'''
Building an index, then a DataFrame

You can also build the DataFrame and index independently, and then put them together. If you take this route, be careful, as any mistakes in generating the DataFrame or the index can cause the data and the index to be aligned incorrectly.

In this exercise, the sales DataFrame has been provided for you without the month index. Your job is to build this index separately and then assign it to the sales DataFrame. Before getting started, print the sales DataFrame in the IPython Shell and note that it's missing the month information.

INSTRUCTIONS
100XP
Generate a list months with the data ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']. This has been done for you.
Assign months to sales.index.
Print the modified sales dataframe and verify that you now have month information in the index.
'''
# Generate the list of months: months
months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']

# Assign months to sales.index
sales.index = months

# Print the modified sales DataFrame
print(sales)

'''
Building an index, then a DataFrame

You can also build the DataFrame and index independently, and then put them together. If you take this route, be careful, as any mistakes in generating the DataFrame or the index can cause the data and the index to be aligned incorrectly.

In this exercise, the sales DataFrame has been provided for you without the month index. Your job is to build this index separately and then assign it to the sales DataFrame. Before getting started, print the sales DataFrame in the IPython Shell and note that it's missing the month information.

INSTRUCTIONS
100XP
Generate a list months with the data ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']. This has been done for you.
Assign months to sales.index.
Print the modified sales dataframe and verify that you now have month information in the index.
'''
# Generate the list of months: months
months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']

# Assign months to sales.index
sales.index = months

# Print the modified sales DataFrame
print(sales)

Building an index, then a DataFrame  You can also build the DataFrame and index independently, and then put them together. If you take this route, be careful, as any mistakes in generating the DataFrame or the index can cause the data and the index to be aligned incorrectly.  In this exercise, the sales DataFrame has been provided for you without the month index. Your job is to build this index separately and then assign it to the sales DataFrame. Before getting started, print the sales DataFrame in the IPython Shell and note that it's missing the month information.  INSTRUCTIONS 100XP Generate a list months with the data ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']. This has been done for you. Assign months to sales.index. Print the modified sales dataframe and verify that you now have month information in the index. # Generate the list of months: months # Assign months to sales.index # Print the modified sales DataFrame