How to extract date from Excel file using Pandas?
Last Updated :
02 Jan, 2023
Prerequisite: Regular Expressions in Python
In this article, Let’s see how to extract date from the Excel file. Suppose our Excel file looks like below given image then we have to extract the date from the string and store it into a new Dataframe column.
date_sample_data.xlsx
For viewing the Excel file Click Here.
Approach :
- Import required module.
- Import data from Excel file.
- Make an extra column for a new date.
- Set Index for searching.
- Define the pattern of date format.
- Search Date and assigning to the respective column in Dataframe.
Let’s see Step-By-Step-Implementation:
Step 1: Import the required module and read data from the Excel file.
Python3
import pandas as pd;
import re;
data = pd.read_excel("date_sample_data.xlsx");
print("Original DataFrame")
data
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Output:
Step 2: Make an extra column for a new date.
Python3
data['new_Date']= None
data
|
Output:
Step 3: Set Index for searching.
Python3
index_set = data.columns.get_loc('Description')
index_date = data.columns.get_loc('new_Date')
print(index_set, index_date)
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Output:
1 2
Step 4: Defining the Pattern of the date format.
We need to create a Regular expression for date pattern in DD/MM/YY format. Use the [0-9] expression to find any character between the brackets that is a digit. Use escape sequence “\” for escaping “/” a special symbol and {2}, {4} is used to denote no of times a character belongs to the given string. So the expression become ‘[0-9]{2}\/[0-9]{2}\/[0-9]{4}’.
Example:
02/04/2020
02 -----> [0 to 9] --> [0-9]
number of character inside the string {2} ( i.e DD)
04- ----> [0 to 9] --> [0-9]
number of character inside the string {2} ( i.e MM)
2020 -->[0 to 9] -->[0-9]
number of character inside the string {4} ( i.e YYYY)
Python3
date_pattern = r'([0-9]{2}\/[0-9]{2}\/[0-9]{4})'
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Step 5: Search Date and assigning to the respective column in Dataframe.
For searching the Date using regex in a string we are using re.search() function of re library.
Python3
for row in range(0, len(data)):
Date = re.search(date_pattern,data.iat[row,index_set]).group()
data.iat[row, index_date] = Date
data
|
Output:
Complete Code:
Python3
import pandas as pd;
import re;
data = pd.read_excel("date_sample_data.xlsx");
print("Original data : \n",
data)
data['new_Date'] = None
index_set = data.columns.get_loc('Description')
index_date = data.columns.get_loc('new_Date')
print(index_set, index_date)
date_pattern = r'([0-9]{2}\/[0-9]{2}\/[0-9]{4})'
for row in range(0, len(data)):
Date = re.search(date_pattern,
data.iat[row,index_set]).group()
data.iat[row, index_date] = Date
data
|
Output:
Note: Before running this program, make sure you have already installed xlrd library in your Python environment.
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