How to pivot a dataframe in Pandas?

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?

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Answers:

Method 1

Method 2

Answers:

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Method 1

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

Method 2

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.

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