Some Usefull Pandas Formula

 # data.info()

use for displaying Column Name,[Data type], null/Non/Null

#data.describe().T

use to display Mean,Median Mode, Percentile,Min and max Value

#data.corr().style.background_gradient(cmap='coolwarm')

use to Display and Calculate Correlation among Columns,

#data.isna()

for finding null value in columns

#data.isna().sum()

for displaying total null values in columns

#data['classification'].unique()

to display Unique Value

#data[['classification','id']].groupby('classification').count()

to display Count value group by naother column

#data.drop(['id','rbc'],axis=1,inplace=True)

droping Columns

#data['age'].mean()

calculating Mean of Column

#data['dm'].replace(to_replace = {' yes':'yes'},inplace=True)

replacing a value with another value

#data['appet'].fillna( data['appet'].mode()[0], inplace=True)

Filling Null Value with Mode

# for col in data.columns:

    print(f"{col} has {data[col].unique()} values\n")

Displaying all columns Unique Value

#

g = sns.PairGrid(data)

g.map_diag(plt.hist)

g.map_offdiag(plt.scatter)

Displaying Pair Plot

#sns.catplot(x="classification", y="age",data=data,hue='appet',col='htn')

Displaying Category Plot

#sns.boxplot(x='htn',y='age',data=notchk_age)

Displaying Box Plot