Data Science va Sun'iy Intellekt Praktikum

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns # agar seaborn o'rnatilmagan bo'lsa pip install seaborn

x = np.arange(0, 4 * np.pi, 0.1)
sin = np.sin(x) # sin(x)
cos = np.cos(x) # cos(x)

plt.figure(figsize=(12,6))
plt.subplot(2,1,1) # 2 - jami qatorlar soni, 1 - jami ustunlar soni, 1-grafik
# sin(x) grafigi
plt.plot(x, sin,
         linewidth=1.5,
         linestyle='-.',
         color='#8E44AD',
         alpha=0.7,
         marker='h')
plt.title('sin(x) funksiya grafigi')
plt.grid(color='tomato', alpha=0.5, linestyle='--') # setkani o'zgartirish

plt.subplot(2,1,2) # # 2 - jami qatorlar soni, 1 - jami ustunlar soni, 2-grafik
# cos(x) grafigi
plt.plot(x, cos,
         linewidth=1.5,
         linestyle=':',
         color='c',
         alpha=0.7,
         marker='v')
plt.title('cos(x) funksiya grafigi')
plt.grid(color='tomato', alpha=0.5, linestyle='--') # setkani o'zgartirish

plt.show()

df = pd.read_csv("https://raw.githubusercontent.com/anvarnarz/praktikum_datasets/main/merc.csv")
df=df[df.year>=2010] # 2010-yildan keyin chiqqan mashinalarni saqlab qolamiz
df=df[df.transmission!='Other'] # Faqat avtomat, mexanik va yarim-avtomat mashinalarni olib qolamiz
df=df[df.fuelType!='Other'] # Faqat benzin, dizel va gibrid mashinalarni olib qolamiz
df.head()