CODEWITHSUNDEEP
pythonpandasmultiple-columnsswap
Yun Tae Hwang
Yun Tae Hwang

Reputation: 1471

pandas how to swap or reorder columns

I know that there are ways to swap the column order in python pandas. Let say I have this example dataset:

import pandas as pd    
employee = {'EmployeeID' : [0,1,2],
     'FirstName' : ['a','b','c'],
     'LastName' : ['a','b','c'],
     'MiddleName' : ['a','b', None],
     'Contact' : ['(M) 133-245-3123', '(F)[email protected]', '(F)312-533-2442 [email protected]']}

df = pd.DataFrame(employee)

The one basic way to do would be:

neworder = ['EmployeeID','FirstName','MiddleName','LastName','Contact']
df=df.reindex(columns=neworder)

However, as you can see, I only want to swap two columns. It was doable just because there are only 4 column, but what if I have like 100 columns? what would be an effective way to swap or reorder columns?

There might be 2 cases:

  1. when you just want 2 columns swapped.
  2. when you want 3 columns reordered. (I am pretty sure that this case can be applied to more than 3 columns.)

Upvotes: 51

Views: 127043

Answers (9)

KDL4ever
KDL4ever

Reputation: 21

Here's a two line solution which will work regardless of the size of the dataframe (no matter how many columns are there) as long as you know the names of the columns you want to swap. If the two columns are "col1" and "col2" in your dataframe (df):

df['col1'], df['col2'] = df['col2'].values, df['col1'].values
df = df.rename(columns={'col1': 'temp_col1', 'col2': 'col1', 'temp_col1': 'col2'})

Upvotes: 0

SAM NIJIN
SAM NIJIN

Reputation: 11

Positioning the pandas series according to need

#using pandas.iloc
df.iloc[:,[1,3,2,0]]

the first param of the pandas.iloc function is meant for rows, and the second param is meant for columns so we had given a list of order in which the columns has to be displayed.

Upvotes: 0

jvaldiviezo
jvaldiviezo

Reputation: 101

I think a function like this will be very useful to have control over the position of the columns:

def df_changeorder(frame: pd.DataFrame, var: list, remove=False, count_order='left', offset=0) -> pd.DataFrame:
    """
    :param frame: dataframe
    :param var: list of columns to move to the front
    :param count_order: where to start counting from left or right to insert
    :param offset: cols to skip in the count_order specified
    :return: dataframe with order changed
    """

    varlist = [w for w in frame.columns if w not in var]

    if remove:
        frame = frame[var]
    else:

        if offset == 0:

            if count_order == 'left':

                frame = frame[var + varlist]

            if count_order == 'right':

                frame = frame[varlist + var]

        else:
            if count_order == 'left':
                frame = frame[varlist[:offset] + var + varlist[offset:]]

            if count_order == 'right':
                frame = frame[varlist[:-offset] + var + varlist[-offset:]]

    return frame

A simple use case will be like defining the columns we want to reorder, for example, using the provided DataFrame, if we wanted to make this order:

['EmployeeID', 'Contact', 'LastName', 'FirstName', 'MiddleName']

Notice we only need to move Contact and LastName, therefore we can have that result easily as:

# columns to swap
swap_columns = ["Contact","LastName"]

# change the order
df = df_changeorder(df, swap_columns, count_order='left', offset=1)

With this approach we can reorder as many columns as we want, we just need to specify the list of columns and then apply the function as in the example.

Upvotes: 0

jeffhale
jeffhale

Reputation: 4032

A concise way to reorder columns when you don't have too many columns and don't want to list the column names is with .iloc[].

df_reorderd = df.iloc[:, [0, 1, 3, 2, 4]]

Upvotes: 3

Serge Stroobandt
Serge Stroobandt

Reputation: 31508

When writing to a file

Columns can also be reordered when the dataframe is written out to a file (e.g. CSV):

df.to_csv('employees.csv',
          columns=['EmployeeID','FirstName','MiddleName','LastName','Contact'])

Upvotes: 1

Jean-Francois T.
Jean-Francois T.

Reputation: 12930

If you want to have a fixed list of columns at the beginning, you could do something like

cols = ['EmployeeID','FirstName','MiddleName','LastName']
df = df[cols + [c for c in df.columns if c not in cols]]

This will put these 4 columns first and leave the rest untouched (without any duplicate column).

Upvotes: 20

rssmith01
rssmith01

Reputation: 131

When faced with same problem at larger scale, I came across a very elegant solution at this link: http://www.datasciencemadesimple.com/re-arrange-or-re-order-the-column-of-dataframe-in-pandas-python-2/ under the heading "Rearrange the column of dataframe by column position in pandas python".

Basically if you have the column order as a list, you can read that in as the new column order. 

##### Rearrange the column of dataframe by column position in pandas python

df2=df1[df1.columns[[3,2,1,0]]]
print(df2)

In my case, I had a pre-calculated column linkage that determined the new order I wanted. If this order was defined as an array in L, then:

a_L_order = a[a.columns[L]]

Upvotes: 13

sanster9292
sanster9292

Reputation: 1325

Say your current order of column is [b,c,d,a] and you want to order it into [a,b,c,d], you could do it this way:

new_df = old_df[['a', 'b', 'c', 'd']]

Upvotes: 78

Vivek Kalyanarangan
Vivek Kalyanarangan

Reputation: 9081

Two column Swapping 

cols = list(df.columns)
a, b = cols.index('LastName'), cols.index('MiddleName')
cols[b], cols[a] = cols[a], cols[b]
df = df[cols]

Reorder column Swapping (2 swaps)

cols = list(df.columns)
a, b, c, d = cols.index('LastName'), cols.index('MiddleName'), cols.index('Contact'), cols.index('EmployeeID')
cols[a], cols[b], cols[c], cols[d] = cols[b], cols[a], cols[d], cols[c]
df = df[cols]

Swapping Multiple

Now it comes down to how you can play with list slices - 

cols = list(df.columns)
cols = cols[1::2] + cols[::2]
df = df[cols]

Upvotes: 37

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