Swedish Auto Insurance Dataset

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Updated 4 years ago

1. Introduction

The Swedish Auto Insurance Dataset involves predicting the total payment for all claims in thousands of Swedish Kronor, given the total number of claims.
It is a regression problem. It is comprised of 63 observations with 1 input variable and one output variable. The variable names are as follows:

Number of claims.

Total payment for all claims in thousands of Swedish Kronor.

## Loading the dataset from github repo

import warnings
warnings.filterwarnings("ignore")
import pandas as pd

url='https://raw.githubusercontent.com/hargurjeet/MachineLearning/Swedish-Auto-Insurance-Dataset/insurance.csv'

df_raw=pd.read_csv(url,sep='delimiter', header=None,  engine='python')

## Dropping intial junk values,renaming the column and resetting the index values
df = df_raw.drop([0, 1, 2, 3], axis=0).reset_index(drop=True).rename(columns={0:'No_Of_Claims'})
df = df.No_Of_Claims.str.split(',',expand=True).rename(columns={0:'No_Of_Claims', 1:'Total_Payment'})
df.head()

df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 63 entries, 0 to 62
Data columns (total 2 columns):
 #   Column         Non-Null Count  Dtype 
---  ------         --------------  ----- 
 0   No_Of_Claims   63 non-null     object
 1   Total_Payment  63 non-null     object
dtypes: object(2)
memory usage: 1.1+ KB