Cannot convert string to float in pandas (ValueError)

These strings have commas as thousands separators so you will have to remove them before the call to float:

df[column] = (df[column].str.split()).apply(lambda x: float(x[0].replace(',', '')))

This can be simplified a bit by moving split inside the lambda:

df[column] = df[column].apply(lambda x: float(x.split()[0].replace(',', '')))

Another solution with list comprehension, if need apply string functions working only with Series (columns of DataFrame) like str.split and str.replace:

df = pd.concat([df[col].str.split()
                       .str[0]
                       .str.replace(',','').astype(float) for col in df], axis=1)

#if need convert column Purchase count to int
df['Purchase count'] = df['Purchase count'].astype(int)
print (df)
         Total Revenue  Average Revenue  Purchase count  Rate
Date                                                        
Monday         1304.4            20.07            2345  1.54

I have also faced that problem and my problem was resolved using the code below:

import pandas as pd
df['Purchase count'] = pd.to_numeric(df['Purchase count'], errors='coerce')
print(df.dtypes)

the below solution worked for me..!!

import pandas as pd


df['Purchase count'] = df['Purchase count'].replace(',', '', regex=True).astype(float)

print('type:    ', type(df['Purchase count']))