PYTHON

change 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'])

how to change the column order in pandas dataframe

df = df.reindex(columns=column_names)

python change column order in dataframe

cols = df.columns.tolist()
cols = cols[-1:] + cols[:-1] #bring last element to 1st position
df = df.reindex(cols, axis=1)

pandas change column order

df[['column2', 'column3', 'column1']]

reorder columns pandas

cols = df.columns.tolist()
# Rearrange the list any way you want
cols = cols[-1:] + cols[:-1]
df = df[cols]

change dataframe columns order

df = df[['col1', 'col2', 'col3', 'col4']]

rearrange columns pandas

You could also do something like this:

df = df[['mean', '0', '1', '2', '3']]
You can get the list of columns with:

cols = list(df.columns.values)
The output will produce:

['0', '1', '2', '3', 'mean']

change column order pandas

# Want to change column3 to show up first
df = pd.Dataframe({
  "column1":(1,2,3),
  "column2":(4,5,6),
  "column3":(7,8,9)
}
# From all solutions I could find, this seems to be the best performance wise:
col = df.pop(col_name)
df.insert(0, col.name, col)# <- works in place and returns None (at least for me)
  

how to reorder columns in pandas

Reorder columns in pandas

pandas change column order

frame = frame[['column I want first', 'column I want second'...etc.]]

python pandas change column order

In [39]: df
Out[39]: 
          0         1         2         3         4  mean
0  0.172742  0.915661  0.043387  0.712833  0.190717     1
1  0.128186  0.424771  0.590779  0.771080  0.617472     1
2  0.125709  0.085894  0.989798  0.829491  0.155563     1
3  0.742578  0.104061  0.299708  0.616751  0.951802     1
4  0.721118  0.528156  0.421360  0.105886  0.322311     1
5  0.900878  0.082047  0.224656  0.195162  0.736652     1
6  0.897832  0.558108  0.318016  0.586563  0.507564     1
7  0.027178  0.375183  0.930248  0.921786  0.337060     1
8  0.763028  0.182905  0.931756  0.110675  0.423398     1
9  0.848996  0.310562  0.140873  0.304561  0.417808     1

In [40]: df = df[['mean', 4,3,2,1]]