I have tried many things to create a Python dataframe from 4 variables on a csv file: Date (mm/dd/yyyy format), floating point variables Reserves, FF, IORB. All tries result in error message that I haven't identified column with the data (apologies if my terminology is not correct). I found some easy errors to fix. Now from a df.columns, the name of my df is rates, I see the correct data names Date, Reserves, FF, IORB. I even renamed the dataframe 'rates' names. But statements with these names are errors, that the variable isn't defined. This is first time I've imported a CSV file into Python

from datetime import datetime   
import matplotlib.pyplot as plt  
import numpy as np 
import pandas as pd 
import dateparser 
d= lambda x: pd.datetime.strptime(x, '%m/%w/%Y')  
dateparse = lambda x: d(x) 
rates = pd.read_csv(r'C:/Users/Owner/Documents/Research/SOMA/SomaFinal.csv','./data.txt', index_col=[0],\ usecols=[0,1,2,3],skiprows=6, parse_dates=['Date'])) 
print(rates.columns) 
rates.info()  
rates = rates.rename(columns={'rates[1]': 'Reserves', 'rates[2]': 'FF', 'rates[3]': 'IORB'})
print(FF) 

**ERROR: File "C:\Users\Owner\Documents\Research\SOMA\soma.py", line 27, in print(FF) NameError: name 'FF' is not defined

Output:

Index(['Date', 'WRESBAL', 'FF', 'IORB'], dtype='object')
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1999 entries, 0 to 1998
Data columns (total 4 columns):
 #   Column   Non-Null Count  Dtype         
---  ------   --------------  -----         
 0   Date     1992 non-null   datetime64[ns]
 1   WRESBAL  1992 non-null   float64       
 2   FF       1992 non-null   float64       
 3   IORB     39 non-null     object        
dtypes: datetime64[ns](1), float64(2), object(1)
memory usage: 62.6+ KB
6


<class 'pandas.core.frame.DataFrame'>

RangeIndex: 2005 entries, 0 to 2004