Lab | Customer Analysis Round 1

[joaomatoslopes]

This repository contain a jupyter file with my answers regarding the Lab (Customer Analysis Round 1)

[pt-data-ta-lis]

Good Job!

Comments:

• Rearrange the columns in the dataframe as needed
  data_file2 = data_file2[data_file1.columns]
  data_file3 = data_file3[data_file1.columns]

• Which columns are numerical?
  data_concatenated.select_dtypes('float')

• Which columns are categorial?
  data_concatenated.select_dtypes('object')

• Correct the values in the column customer_lifetime_value. They are given as percent, so multiply them by 100 and change dtype to numerical type
  data_concat['customer_lifetime_value'] = data_concat['customer_lifetime_value'].str.replace('%','')
  data_concat['customer_lifetime_value'] = pd.to_numeric(data_concat['customer_lifetime_value'], errors='coerce')*100

• Filter out the data for customers who have an income of 0 or less
  Intendend to take out who has an income of 0 or less so that the final data frame shows only who has a positive income.
  data_concat = data_concat[data_concat['income']>0]