Search⌘ K
Home
Courses
Data Analytics in Python

Converting Percentages to CPI Values

Understand how to adjust wage percentage growth data to align with Consumer Price Index values by creating a Python function. Learn the process of converting annual average wage percentages into quarterly CPI approximations to enable accurate comparisons of economic trends.

We'll cover the following...

How to convert data

Well, that’s our formatting problem out of the way: we’ve converted the CPI data to quarterly increments and cleaned up the Date format to match the wages data. Now we’ll need to address the inconsistency between the absolute point values in the CPI set and the percentages that came with the wages data.

Wages
Python 3.5
import pandas as pd
import matplotlib as plt
import numpy as np
import bls
wages = bls.get_series('CIU2020000000000A')
wages.to_csv('bls_data_csv')
df = pd.read_csv('bls_data_csv')
df.columns = 'Date','Wages'
print (df)

  • Get that data: First, let’s get that data. Technically, if you’ve been following along on your own, you’ll already have pulled the series back near the beginning, but it can’t hurt to rerun it. (line 5)

  • Save the data: Once again, we save the data to a CSV file (which, again, isn’t necessary). (line 6)

  • Push the data: We push the data to a df data frame and give it column headers. (line 7) ...