Group Members

  • Can AYTÖRE

  • Ebru GEÇİCİ

  • Mustafa KESER

  • Nazlı GÜL

  • Taha BAYAZ

  • Talha ÜNLÜ

Overview of the Data

This dataset contains the features and prices of the cars sold online in Turkey, in 2020. This data is obtained from Kaggle in order to make a comprehensive analysis about the online car market. The variables in the data set are as follows: date, brand, vehicle type, model year, fuel type, transmission, CCM, horse power, color, body type, seller, seller status, kilometers, and price. Our main goal is to make the best forecast of the prices using the variables in the data set. In the dataset we have 9044 observations with 15 features. You can find the glimpse of the data below.

car = read.csv("turkey_car_market.csv")
car %>% glimpse()
## Rows: 9,044
## Columns: 15
## $ Ä.lan.Tarihi   <fct> 27/05/2020, 16/06/2020, 14/06/2020, 11/06/2020, 11/0...
## $ Marka          <fct> Jaguar, Acura, Acura, Acura, Acura, Acura, Acura, Ac...
## $ Arac.Tip.Grubu <fct> XF, CL, CL, CL, CL, CL, CL, CL, RSX, RSX, CL, CL, CL...
## $ Arac.Tip       <fct> 2.0 D Prestige Plus, -, 2.2, -, 2.2, 2.2, 2.2, -, Ty...
## $ Model.YÄ.l     <dbl> 2017, 2015, 1994, 2013, 2010, 1999, 2014, 2014, 2019...
## $ YakÄ.t.Turu    <fct> Dizel, Dizel, Benzin/LPG, Dizel, Dizel, Dizel, Dizel...
## $ Vites          <fct> Otomatik Vites, Yarı Otomatik Vites, Düz Vites, DÃ...
## $ CCM            <fct> 1801-2000 cc, 1301-1600 cc, 1301-1600 cc, 1301-1600 ...
## $ Beygir.Gucu    <fct> 176-200 BG, 101-125 BG, 101-125 BG, 76-100 BG, 151-1...
## $ Renk           <fct> Lacivert , Mavi , Turkuaz , Kahverengi , Beyaz , Lac...
## $ Kasa.Tipi      <fct> Hatchback 5 Kapı, Sedan, Sedan, Sedan, Sedan, Roads...
## $ Kimden         <fct> Galeriden, Sahibinden, Sahibinden, Sahibinden, Sahib...
## $ Durum          <fct> 2. El, 2. El, 2. El, 2. El, 2. El, 2. El, 2. El, 2. ...
## $ Km             <int> 26100, 127000, 175000, 325, 207000, 320000, 183, 790...
## $ Fiyat          <int> 634500, 151500, 19750, 52000, 148750, 42500, 170000,...

Plan

Our tentative plan is as below:

  • Cleaning, tidying and manipulating the data

  • Using data visualizations to understand the data better

  • Specifying the most related feature(s) with (the most effective feature(s) on) prices of a car

  • Forecasting the car prices and creating a model

  • To come up with a conclusion

To be able to obey the plan, we will use some packages like;

  • dplyr

  • ggplot2

  • lubridate

  • data.table

  • shiny etc.