sort dataframe by column
df.sort_values(by='col1', ascending=False)sort dataframe by column
df.sort_values(by='col1', ascending=False)df sort values
>>> df.sort_values(by=['col1'], ascending = False)
col1 col2 col3
0 A 2 0
1 A 1 1
2 B 9 9
5 C 4 3
4 D 7 2
3 NaN 8 4change column order dataframe python
# create a dataframe
df = pd.DataFrame({'B':[1,2],'A':[0,0],'C':[1,1]})
# reorder columns as ['A','B','C']
df = df.reindex(columns = ['A','B','C'])dataframe, sort by columns
final_df = df.sort_values(by=['2'], ascending=False)pandas reorder columns
# setting up a dummy dataframe
raw_data = {'name': ['Willard Morris', 'Al Jennings', 'Omar Mullins', 'Spencer McDaniel'],
'age': [20, 19, 22, 21],
'favorite_color': ['blue', 'red', 'yellow', "green"],
'grade': [88, 92, 95, 70]}
df = pd.DataFrame(raw_data, index = ['Willard Morris', 'Al Jennings', 'Omar Mullins', 'Spencer McDaniel'])
df
#now 'age' will appear at the end of our df
df = df[['favorite_color','grade','name','age']]
df.head()sort df by column
df.rename(columns={1:'month'},inplace=True)
df['month'] = pd.Categorical(df['month'],categories=['December','November','October','September','August','July','June','May','April','March','February','January'],ordered=True)
df = df.sort_values('month',ascending=False)Copyright © 2021 Codeinu
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