Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Compare specific Timestamps for a Pandas DataFrame – Python
To compare specific timestamps, use the index number in the square brackets. At first, import the required library −
import pandas as pd
Create a DataFrame with 3 columns. We have two date columns with timestamp −
dataFrame = pd.DataFrame(
{
"Car": ["Audi", "Lexus", "Tesla", "Mercedes", "BMW"],
"Date_of_Purchase": [
pd.Timestamp("2021-06-10"),
pd.Timestamp("2021-07-11"),
pd.Timestamp("2021-06-25"),
pd.Timestamp("2021-06-29"),
pd.Timestamp("2021-03-20"),
],
"Date_of_Service": [
pd.Timestamp("2021-11-05"),
pd.Timestamp("2021-12-03"),
pd.Timestamp("2021-10-30"),
pd.Timestamp("2021-11-29"),
pd.Timestamp("2021-08-20"),
]
})
Find specific Timestamps, let’s say 1 to 3 rows −
timestamp1_diff = abs(dataFrame['Date_of_Purchase'][0]-dataFrame['Date_of_Service'][0]) timestamp2_diff = abs(dataFrame['Date_of_Purchase'][1]-dataFrame['Date_of_Service'][1]) timestamp3_diff = abs(dataFrame['Date_of_Purchase'][2]-dataFrame['Date_of_Service'][2])
Example
Following is the code −
import pandas as pd
# create a dataframe with 3 columns
dataFrame = pd.DataFrame(
{
"Car": ["Audi", "Lexus", "Tesla", "Mercedes", "BMW"],
"Date_of_Purchase": [
pd.Timestamp("2021-06-10"),
pd.Timestamp("2021-07-11"),
pd.Timestamp("2021-06-25"),
pd.Timestamp("2021-06-29"),
pd.Timestamp("2021-03-20"),
],
"Date_of_Service": [
pd.Timestamp("2021-11-05"),
pd.Timestamp("2021-12-03"),
pd.Timestamp("2021-10-30"),
pd.Timestamp("2021-11-29"),
pd.Timestamp("2021-08-20"),
]
})
print"DataFrame...\n", dataFrame
# compare specific timestamps
timestamp1_diff = abs(dataFrame['Date_of_Purchase'][0]-dataFrame['Date_of_Service'][0])
timestamp2_diff = abs(dataFrame['Date_of_Purchase'][1]-dataFrame['Date_of_Service'][1])
timestamp3_diff = abs(dataFrame['Date_of_Purchase'][2]-dataFrame['Date_of_Service'][2])
print"\nDifference between Car 1 Date of Purchase and Service \n",timestamp1_diff
print"\nDifference between Car 2 Date of Purchase and Service \n",timestamp2_diff
print"\nDifference between Car 3 Date of Purchase and Service \n",timestamp3_diff
Output
This will produce the following output −
DataFrame... Car Date_of_Purchase Date_of_Service 0 Audi 2021-06-10 2021-11-05 1 Lexus 2021-07-11 2021-12-03 2 Tesla 2021-06-25 2021-10-30 3 Mercedes 2021-06-29 2021-11-29 4 BMW 2021-03-20 2021-08-20 Difference between Car 1 Date of Purchase and Service 148 days 00:00:00 Difference between Car 2 Date of Purchase and Service 145 days 00:00:00 Difference between Car 3 Date of Purchase and Service 127 days 00:00:00
Advertisements