This is my data frame.

I want above data frame like bellow using python and panda.

Please help me. Thank You.

CodePudding user response：

You could do this with the pivot method of the dataframe.

Code

The following code assumes the original data is in a file named test.csv.

import pandas as pd

df = pd.read_csv('test.csv')

print(df)

df = df.pivot(index='Date', columns='Country', values = 'Value').reset_index()

print(df)

Before

After

CodePudding user response：

Here we create your dataframe for test..

import pandas as pd

arr = [['1/4/1971', 'Sweden', '5.1643'],
       ['1/5/1971', 'Sweden', '5.1628'],
       ['1/6/1971', 'Sweden', '5.1614'],
       ['1/7/1971', 'Sweden', '5.1649'],
       ['1/8/1971', 'Sweden', '5.1631'],
       ['1/4/1971', 'Canada', '1.0109'],
       ['1/5/1971', 'Canada', '1.0102'],
       ['1/6/1971', 'Canada', '1.0106'],
       ['1/7/1971', 'Canada', '1.0148'],
       ['1/8/1971', 'Canada', '1.0154'],
       ['1/4/1971', 'India', '8.02'],
       ['1/5/1971', 'India', '8.00'],
       ['1/6/1971', 'India', '8.01'],
       ['1/7/1971', 'India', '8.00'],
       ['1/8/1971', 'India', '8.03']]
df = pd.DataFrame(arr,columns=['Date','Country','Value'])
print('old form')
print(df)

The output should be like:

old form
        Date Country   Value
0   1/4/1971  Sweden  5.1643
1   1/5/1971  Sweden  5.1628
2   1/6/1971  Sweden  5.1614
3   1/7/1971  Sweden  5.1649
4   1/8/1971  Sweden  5.1631
5   1/4/1971  Canada  1.0109
6   1/5/1971  Canada  1.0102
7   1/6/1971  Canada  1.0106
8   1/7/1971  Canada  1.0148
9   1/8/1971  Canada  1.0154
10  1/4/1971   India    8.02
11  1/5/1971   India    8.00
12  1/6/1971   India    8.01
13  1/7/1971   India    8.00
14  1/8/1971   India    8.03

Let's do our magic:

note: this code not optimized but works well

table = {}
for row in df.values:
    date = row[0]
    country = row[1]
    value = row[2]
    if date not in table:table[date] = {country:value}
    else:table[date][country] = value

arr = []
for date in table.keys():
    row = table[date]
    row = [date,row['Sweden'],row['Canada'],row['India']]
    arr.append(row)

df2 = pd.DataFrame(arr,columns=['Date','Sweden','Canada','India'])
print('new form')
print(df2)    

The final output should be

new form
       Date  Sweden  Canada India
0  1/4/1971  5.1643  1.0109  8.02
1  1/5/1971  5.1628  1.0102  8.00
2  1/6/1971  5.1614  1.0106  8.01
3  1/7/1971  5.1649  1.0148  8.00
4  1/8/1971  5.1631  1.0154  8.03