Analysis3.py

# coding: utf-8

# In[1]:

# get_ipython().magic('matplotlib inline')


# In[2]:

# importing required libraries
import os
import subprocess
import stat
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from datetime import datetime
sns.set(style="white")


# In[3]:

# absolute path till parent folder
abs_path = os.getcwd()
path_array = abs_path.split("/")
path_array = path_array[:len(path_array)-1]
homefolder_path = ""
for i in path_array[1:]:
    homefolder_path = homefolder_path + "/" + i 


# In[4]:

# path to clean data
clean_data_path = homefolder_path + "/CleanData/CleanedDataSet/cleaned_autos.csv"

# reading csv into raw dataframe
df = pd.read_csv(clean_data_path,encoding="latin-1")


# ## Average price of vehicle by fuel type and gearbox type

# In[9]:

# barplot for price based on fuel type and gearbox type
fig, ax = plt.subplots(figsize=(8,5))
colors = ["#00e600", "#ff8c1a","#a180cc"]
sns.barplot(x="fuelType", y="price",hue="gearbox", palette="husl",data=df)
ax.set_title("Average price of vehicles by fuel type and gearbox type")
plt.show()


# In[8]:

# saving the plot
fig.savefig((abs_path + "/Plots/vehicletype-fueltype-price.png"))


# ## Average power of a vehicle by vehicle type and gearbox type 

# In[18]:

# barplot for price based on fuel type and gearbox type
colors = ["windows blue", "amber", "greyish", "faded green", "dusty purple"]
fig, ax = plt.subplots(figsize=(8,5))
sns.set_palette(sns.xkcd_palette(colors))
sns.barplot(x="vehicleType", y="powerPS",hue="gearbox",data=df)
ax.set_title("Average price of vehicles by fuel type and gearbox type")
plt.show()


# In[19]:

# saving the plot
fig.savefig((abs_path + "/Plots/vehicletype-fueltype-power.png"))


# In[ ]: