I have a table in csv format that looks like this. I would like to transpose the table so that the values in the indicator name column are the new columns,

Indicator Country Year Value 1 Angola 2005 6 2 Angola 2005 13 3 Angola 2005 10 4 Angola 2005 11 5 Angola 2005 5 1 Angola 2006 3 2 Angola 2006 2 3 Angola 2006 7 4 Angola 2006 3 5 Angola 2006 6

I would like the end result to like like this:

Country Year 1 2 3 4 5 Angola 2005 6 13 10 11 5 Angola 2006 3 2 7 3 6

I have tried using a pandas data frame with not much success.

print(df.pivot(columns = 'Country', 'Year', 'Indicator', values = 'Value'))

Any thoughts on how to accomplish this?

3

2 Answers

You can use pivot_table:

pd.pivot_table(df, values = 'Value', index=['Country','Year'], columns = 'Indicator').reset_index()

this outputs:

 Indicator Country Year 1 2 3 4 5 0 Angola 2005 6 13 10 11 5 1 Angola 2006 3 2 7 3 6
3

This is a guess: it's not a ".csv" file, but a Pandas DataFrame imported from a '.csv'.

To pivot this table you want three arguments in your Pandas "pivot". e.g., if df is your dataframe: 

table = df.pivot(index='Country',columns='Year',values='Value') print (table)

This should should give the desired output.

0