Shift Column in a Pandas DataFrame

We can use the shift() method in Pandas to shift the columns of a DataFrame without having to rewrite the whole DataFrame. shift() takes the following parameters

shift(self, periods=1, freq=None, axis=0, fill_value=None)

• periods  Number of periods to shift. It can take a negative number too.
• axis  It takes a Boolean value; 0 if you want to shift index and 1 if you want to shift column
• fill_value  It will replace the missing value.

Let's take an example and see how to use this shift() method.

Steps

• Create a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.
• Print the input DataFrame, df.
• Select a column and shift it by using df["column_name]=df.column_name.shift()
• Print the updated DataFrame.

Example

import pandas as pd

df = pd.DataFrame(
   dict(
      name=['John', 'Jacob', 'Tom', 'Tim', 'Ally'],
      marks=[89, 23, 100, 56, 90],
      subjects=["Math", "Physics", "Chemistry", "Biology", "English"]
   )
)

print "Input DataFrame is:\n", df

df["name"] = df.name.shift(1)
print "After shifting column name by 1:\n", df

df["marks"] = df.marks.shift(2)
print "After shifting column marks by 2:\n", df

df["subjects"] = df.subjects.shift(-1)
print "After shifting column subjects by -1:\n", df

Output

Input DataFrame is:
     name   marks   subjects
0    John    89         Math
1   Jacob    23      Physics
2     Tom   100    Chemistry
3     Tim    56      Biology
4    Ally    90      English

After shifting column name by 1:
     name   marks   subjects
0     NaN    89         Math
1    John    23      Physics
2   Jacob   100    Chemistry
3     Tom    56      Biology
4     Tim    90      English

After shifting column marks by 2:
     name   marks   subjects
0     NaN    100       Math
1    John    100    Physics
2   Jacob     89  Chemistry
3     Tom     23    Biology
4     Tim    100    English

After shifting column subjects by -1:
     name   marks   subjects
0     NaN   100      Physics
1    John   100    Chemistry
2   Jacob    89      Biology
3     Tom    23      English
4     Tim   100          NaN