import pandas as pd
data = {
'score_1': [30, 40, 25, 19, 60, 15],
'score_2': [3, 7, 9, 2, 5, 11]
}
# create dataframe
df = pd.DataFrame(data)
# sort DataFrame - ascending order
result = df.sort_values(by='score_1')
print(result)
Output
score_1 score_2
5 15 11
3 19 2
2 25 9
0 30 3
1 40 7
4 60 5
We are using the sort_values() function of DataFrame to sort row values in ascending and descending order. By default, the function sort the values in ascending order. if you want to sort the values in descending order, you can pass asending=False to the sort_values() function.
To sort a Dataframe by multiple columns values, we can pass the list of column names that you want to sort in the "by" argument of sort_values() function.
import pandas as pd
data = {
'score_1': [30, 40, 25, 19, 60, 15],
'score_2': [3, 7, 9, 2, 5, 11]
}
# create dataframe
df = pd.DataFrame(data)
# sort DataFrame by multiple columns
result = df.sort_values(by=['score_1', 'score_2'])
print(result)
Output
score_1 score_2
5 15 11
3 19 2
2 25 9
0 30 3
1 40 7
4 60 5
When we use the sort_values() function of DataFrame to sort the column values, it will sort them in ascending order by default. To sort the values in descending order, set ascending=False. Check the below example for reference
Code Example
import pandas as pd
data = {
'company': ['Devsheet', 'Tesla', 'Microsoft', 'Amazon', 'SpaceX'],
'value': [20, 50, 30, 90, 10]
}
# create dataframe
df = pd.DataFrame(data)
# sort DataFrame in descending order
result = df.sort_values(by='value', ascending=False)
print(result)
Output
company value
3 Amazon 90
1 Tesla 50
2 Microsoft 30
0 Devsheet 20
4 SpaceX 10
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