DataFrame.loc[] - ( Pandas Data Operations and Processing )
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Syntax
DataFrame.loc[row_indexer, column_indexer]
Example
import pandas as pd
data = {'name': ['John', 'Jack', 'Alice', 'Bob'],
'age': [24, 32, 19, 45],
'gender': ['M', 'M', 'F', 'M']}
df = pd.DataFrame(data)
df.set_index('name', inplace=True)
# selecting a row using loc
john_info = df.loc['John']
print(john_info)
Output
age 24
gender M
Name: John, dtype: object
Explanation
DataFrame.loc[]
is a Pandas method that is used to access a group of rows and columns by labels or a boolean array.
In the above example, we create a Pandas DataFrame with three columns name
, age
, and gender
. We then set the index of the DataFrame to the name
column using the set_index()
method.
We then use df.loc['John']
to select a row of data for the person with the name 'John'
. This returns a Pandas series object with the age
and gender
columns for the person with the name 'John'
.
Use
DataFrame.loc[]
is a powerful method in Pandas that allows users to select rows and columns of data by labels. This method can be used to filter, slice, and manipulate data in a Pandas DataFrame with great flexibility.
Important Points
DataFrame.loc[]
is used to access a group of rows and columns by labels or a boolean array- It takes in a row indexer and a column indexer
- It returns a Pandas series or DataFrame object depending on the input
Summary
In conclusion, DataFrame.loc[]
is a useful method in Pandas that allows users to access a group of rows and columns by labels. It can be used to filter, slice, and manipulate data in a Pandas DataFrame with great flexibility. The method returns a Pandas series or DataFrame object depending on the input.