Display Start and End Dates for Percent Diff in Python

In this article, we will explore how to display start and end dates for percent diff in Python using the pandas library.

Introduction

The problem at hand is to find the percent diff and difference between consecutive values in a dataset. The desired output should include the dates being compared. We will use the pandas library to sort and group the data, and then calculate the required columns.

Data Preparation

First, we need to import the necessary libraries and load the sample data into a pandas DataFrame.

import pandas as pd
import io

df = pd.read_csv(io.StringIO("""
id    date         value
1     11/01/2020   10
2     11/01/2020   5
1     10/01/2020   20
2     10/01/2020   30
1     09/01/2020   15
2     09/01/2020   10
3     11/01/2020   5
"""), sep=r"\s{2,}", engine="python")

df["date"] = pd.to_datetime(df["date"])

Sorting and Grouping

Next, we need to sort the data by id, date, and value. This will ensure that the data is in the correct order for our calculations.

df2 = df.sort_values(["id", "date", "value"])
gp_obj = df2.groupby("id")

Calculating Required Columns

Now we can calculate the required columns: startdate, diff, and percent. We will use the shift function to get the previous value for each row.

# produce the required columns
df2["startdate"] = gp_obj["date"].shift()
df2["diff"] = gp_obj["value"].diff()
df2["percent"] = df2["diff"] / df2["value"].shift() * 100

Dropping NA Rows and Reorganizing

After calculating the required columns, we need to drop any rows with missing values in the diff column. We also need to rename the date column to enddate.

# drop NA rows and reorganize
df2.rename(columns={"date": "enddate"}, inplace=True)
df2 = df2[["id", "startdate", "enddate", "diff", "percent"]][~df2["diff"].isna()]

Output

Finally, we can print the resulting DataFrame to see the desired output.

print(df2)
   id  startdate    enddate  diff     percent
2   1 2020-09-01 2020-10-01   5.0   33.333333
0   1 2020-10-01 2020-11-01 -10.0  -50.000000
3   2 2020-09-01 2020-10-01  20.0  200.000000
1   2 2020-10-01 2020-11-01 -25.0  -83.333333

Conclusion

In this article, we learned how to display start and end dates for percent diff in Python using the pandas library. We sorted and grouped the data, calculated the required columns, dropped NA rows and reorganized the data, and finally printed the resulting DataFrame. This code can be used as a starting point for more complex data analysis tasks.

Additional Tips

The shift function is used to get the previous value in the series.
The groupby function is used to group the data by id.
The sort_values function is used to sort the data by id, date, and value.
The renames function is used to rename columns in a DataFrame.
The print function is used to display the resulting DataFrame.

References

Last modified on 2023-07-28