Automobile Data Analysis

Python

Using Python for exploratory data analysis

Problem:

What are the main characteristics which have the most impact on the car price?


Exploratory Data Analysis with Python

What features have the most impact on the car price?


## Import Libraries import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt %matplotlib inline
# Data Loading df = pd.read_csv('Auto_mobile.csv')
df.head()
automobile dashboard
Automobile data

Access Exploratory Analytical Report HERE


Conclusion:

At this point, we have gained a more comprehensive understanding of the characteristics of our data, as well as the key variables that should be considered when attempting to forecast car prices. Specifically, we have identified a set of continuous numerical variables, such as length, width, curb-weight, engine-size, horsepower, city-mpg, highway-mpg, wheel-base, and bore, As well as a categorical variable, namely, drive-wheels.


Now, we can use this to construct machine learning models to facilitate our analysis, supplying the model with relevant variables that have a genuine impact on our target variable would enhance the accuracy of our model's predictions.


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