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Pandas DataFrame.loc[]

Pandas DataFrame.loc[] with What is Python Pandas, Reading Multiple Files, Null values, Multiple index, Application, Application Basics, Resampling, Plotting the data, Moving windows functions, Series, Read the file, Data operations, Filter Data etc.

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Pandas DataFrame.loc[]

The DataFrame.loc[] is used to retrieve the group of rows and columns by labels or a boolean array in the DataFrame. It takes only index labels, and if it exists in the caller DataFrame, it returns the rows, columns, or DataFrame.

The DataFrame.loc[] is a label based but may use with the boolean array.

The allowed inputs for .loc[] are:

  • Single label, e.g.,7 or a. Here, 7 is interpreted as the label of the index.
  • List or array of labels, e.g. ['x', 'y', 'z'].
  • Slice object with labels, e.g. 'x':'f'.
  • A boolean array of the same length. e.g. [True, True, False].
  • callable function with one argument.

Syntax

pandas.DataFrame.loc[]

Parameters

None

Returns

It returns Scalar, Series or DataFrame.

Example

# importing pandas as pd

import pandas as pd
# Creating the DataFrame
info = pd.DataFrame({'Age':[32, 41, 44, 38, 33], 
                   'Name':['Phill', 'William', 'Terry', 'Smith', 'Parker']}) 
# Create the index 
index_ = ['Row_1', 'Row_2', 'Row_3', 'Row_4', 'Row_5'] 

# Set the index 
info.index = index_ 

# return the value 
final = info.loc['Row_2', 'Name'] 

# Print the result 
print(final)

Output:

William

Example2:

# importing pandas as pd
import pandas as pd
# Creating the DataFrame
info = pd.DataFrame({"P":[28, 17, 14, 42, None],  
                   "Q":[15, 23, None, 15, 12],  
                   "R":[11, 23, 16, 32, 42],  
                   "S":[41, None, 34, 25, 18]})  
# Create the index 
index_ = ['A', 'B', 'C', 'D', 'E'] 
# Set the index 
info.index = index_ 
# Print the DataFrame
print(info)

Output:

P         Q      R         S
A   28.0    15.0    11   41.0
B   17.0    23.0    23   NaN
C   14.0    NaN    16   34.0
D   42.0   15.0     32   25.0
E NaN    12.0    42   18.0

Now, we have to use DataFrame.loc attribute to return the values present in the DataFrame.

# return the values 
result = info.loc[:, ['P', 'S']] 
# Print the result 
print(result)

Output:

    P    S
A 28.0  41.0
B 17.0   NaN
C14.0  34.0
D  42.0  25.0
ENaN  18.0
Next TopicPandas loc vs iloc




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