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How to extract Time data from an Excel file column using Pandas?

Prerequisite: Regular Expressions in Python

In these articles, we will discuss how to extract Time data from an Excel file column using Pandas. Suppose our Excel file looks like below given image then we have to extract the Time from the Excel sheet column and store it into a new Dataframe column.



For viewing the Excel file Click Here.



Approach:

Let’s see Step-By-Step-Implementation:

Step 1: Import the required module and read data from Excel file.




# importing required module
import pandas as pd;
import re;
  
# Read excel file and store in to DataFrame
data = pd.read_excel("time_sample_data.xlsx");
  
print("Original DataFrame")
data

Output:

Step 2: Make an extra column for storing Time data.




# Create column for Time
data['New time'] = None
data

Output:

Step 3: Set Index for searching 




# set index
index_set = data.columns.get_loc('Description')
index_time = data.columns.get_loc('New time')
  
print(index_set, index_time)

Output:

1 2

Step 4: Defining the Regular expression (regex) for the time.

Regex for time HH/ MM/ SS format: 

[0-24]{2}\:[0-60]{2}\:[0-60]{2}.




# define time pattern
time_pattern = r'([0-24]{2}\:[0-60]{2}\:[0-60]{2})'

Step 5: Search Time and assigning to the respective column in Dataframe.

For searching the time using regex in a string we are using re.search() function of re library.




# searching the entire DataFrame
# with Time pattern
for row in range(0, len(data)):
    
    time = re.search(time_pattern,
                     data.iat[row,index_set]).group()
      
    data.iat[row, index_time] = time
      
print("Final DataFrame")    
data

Output:

Complete Code:




# importing required module
import pandas as pd;
import re;
  
data = pd.read_excel("time_sample_data.xlsx");
print("Original DataFrame")
print(data)
  
# Create column for Date
data['New time']= None
print(data)
  
# set index
index_set= data.columns.get_loc('Description')
index_time=data.columns.get_loc('New time')
print(index_set,index_time)
  
# define the time pattern in HH:MM:SS
time_pattern= r'([0-24]{2}\:[0-60]{2}\:[0-60]{2})'
  
#searching dataframe with time pattern
for row in range(0, len(data)):
    time= re.search(time_pattern,data.iat[row,index_set]).group()
    data.iat[row,index_time] = time
      
print("\n Final DataFrame")    
data

Output:

Note: Before running this program, make sure you have already installed xlrd library in your Python environment.


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