Trier DataFrame par colonne
df.sort_values(by='col1', ascending=False)
Magnificent Moth
df.sort_values(by='col1', ascending=False)df = df[['column1', 'column2','column3']]# 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()#old df columns
df.columns
Index(['A', 'B', 'C', 'D'],dtype='***')
#new column format that we want to rearange
new_col = ['D','C','B','A'] #list of column name in order that we want
df = df[new_col]
df.columns
Index(['D', 'C', 'B', 'A'],dtype='***')
#new column orderIn [7]: cols = df.columns.tolist()
In [8]: cols
Out[8]: [0L, 1L, 2L, 3L, 4L, 'mean']
In [12]: cols = cols[-1:] + cols[:-1]
In [13]: cols
Out[13]: ['mean', 0L, 1L, 2L, 3L, 4L]
In [14]: df = df[cols] # Get column list in ['item1','item2','item3'] format
df.columns
# [0]output:
Index(['item1','item2','item3'], dtype='object')
# Copy just the list portion of the output and rearrange the columns
cols = ['item3','item1','item2']
# Resave dataframe using new column order
df = df[cols]