<jupyter_start><jupyter_text><jupyter_code>import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from google.colab import drive
drive.mount('/content/drive')

data=pd.read_csv('/content/drive/MyDrive/ML/Dataset/mtcars.csv')
d=pd.crosstab(index=data['cyl'],columns="count",dropna=True)
d
data.info()
#Count Total Null values in each column
print("Total Null Data:",data.isnull().sum())
plt.hist(data['mpg'],bins=5)
plt.show()

plt.scatter(data['mpg'],data['wt'])
plt.show()
df=pd.DataFrame(data,columns=['gear'])
print("Count How many values:\n",df['gear'].value_counts())<jupyter_output>Count How many values:
 3    15
4    12
5     5
Name: gear, dtype: int64<jupyter_text>Exercise ------** Exercise: 1.   Draw Scatter Plot between age and salary for "Data_for_Transformation.csv" file2.    Draw Histogramof Salary 3. Plot bar chart of  Country **------<jupyter_code>data = pd.read_csv("/content/drive/MyDrive/ML/Dataset/Data_for_Transformation.csv")
plt.scatter(data['Age'],data['Salary'])
plt.show()
plt.hist(data['Salary'],bins=5)
plt.show()


graph =data['Country'].value_counts().plot(kind='bar')
plt.title("Country with number of count")
plt.xlabel("Country")
plt.ylabel("Number of Count")<jupyter_output><empty_output>
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