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How to shift a 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", dfOutput
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
Updated on: 15-Sep-2021
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