Python Pandas DataFrame Property: loc

In Pandas DataFrame  .loc() method is used to take the index label and return the row or  columns.

.loc() is used to access the groups of rows and columns by using labels or a boolean array.

.loc() method takes only index label and check in dataframe if it exists in the given dataframe it returns the rows, columns or DataFrame.

These are some allowed input for .loc[]:

  • Single label e.g., 9 or 'a'. Here 9 is interpreted as a label of the index.
  • List or array of labels, e.g.['a','b','c']
  • Sliced object with labels.
  • Boolean array with the same length of the axis begin sliced.
  • Callable function with one argument, that can return valid output for indexing.

Syntax

DataFrame.loc

Return:

It return a scalar dataframe or series.

Example

import pandas as pd
df=pd.DataFrame({'Name':['Rohit','Rahul','Alice','John','Joey'],'Age':[16,17,19,15,14],
                 'Height':[150.5,167.9,145.7,152.6,148.7]})#Create DataFrame
index = ['1', '2', '3', '4', '5']#Create  index
df.index=index
print(df)#print the dataframe

Output:

    Name  Age  Height
1  Rohit   16   150.5
2  Rahul   17   167.9
3  Alice   19   145.7
4   John   15   152.6
5   Joey   14   148.7
result = df.loc['3', 'Name']
result#return the value

Output:

'Alice'
result = df.loc[:, ['Name', 'Age']]
result

Output:

  Name Age
1 Rohit 16
2 Rahul 17
3 Alice 19
4 John 15
5 Joey 14
Mon, 11/15/2021 - 09:18

Authored by

Devanshi, is working as a Data Scientist with iVagus. She has expertise in Python, NumPy, Pandas and other data science technologies.