Python panda ppt class XII

Python panda ppt class XII

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1. advance operations on dataframes

2. histogram and qunatiles

3. Function application

4. Reindexing and label alteration

python Pivot, Pivot_table and Sorting a dataframe

Pivot, Pivot_table and dataframe sorting

import numpy as np

import pandas as pd

 

'''

d1 = {'item':['AC','TV','CAR','TV','BIKE','TV'],

      'quantity':[28,36,25,14,25,48],

      'rate':[11,22,33,44,55,66],

      'country':['USA','PAK','JAPAN','USA','INDIA','JAPAN']}

df = pd.DataFrame(d1)

print(df)

#p=df.pivot(index='country', columns='item', values='rate')

p=df.pivot(index='country', columns='item')

print('*'*20)

print(p)

'''

************************************************************

'''

d1 = {'item':['AC','TV','CAR','TV','BIKE','TV'],

      'quantity':[28,36,25,14,25,48],

      'rate':[11,22,33,44,55,66],

      'country':['USA','PAK','JAPAN','USA','INDIA','USA']}

df = pd.DataFrame(d1)

print(df)

#p=df.pivot_table(index='country', columns='item',values='rate')

#p=df.pivot_table(index='country', columns='item',values='rate', aggfunc='mean')

p=df.pivot_table(index='country', columns='item',values='rate', aggfunc='count')

print('*'*20)

print(p)

'''

************************************************************

 

'''

d1 = {'item':['AC','TV','CAR','TV','BIKE','TV'],

      'quantity':[28,36,25,14,25,48],

      'rate':[11,22,33,44,55,66],

      'country':['USA','PAK','JAPAN','USA','INDIA','USA']}

df = pd.DataFrame(d1)

print(df)

#p=df.pivot_table(index=['country','item'],values=['rate','quantity'])

p=df.pivot_table(index=['country','item'],values=['rate'],aggfunc='count')

print('*'*20)

print(p)

'''

 ************************************************************

 

'''

d1 = {'item':['AC','TV','CAR','TV','BIKE','TV'],

      'quantity':[28,36,25,14,25,48],

      'rate':[11,22,33,44,55,66],

      'country':['USA','PAK','JAPAN','USA','INDIA','USA']}

df = pd.DataFrame(d1)

print(df)

print('*'*30)

#print(df.sort_values(['country']))

#print(df.sort_values(['country'], ascending=False))

#print(df.sort_values(['country','item']))

#print(df.sort_values(['country','item'],ascending=False))

#print(df.sort_values(['country','item'], ascending=[False,False]))

print('*'*30)

print(df.sort_values(['country'],inplace=True))

print(df)

'''

************************************************************

 

'''

d1 = {'item':['AC','TV','CAR','TV','BIKE','TV'],

      'quantity':[28,36,25,14,25,48],

      'rate':[11,22,33,44,55,66],

      'country':['USA','PAK','JAPAN','USA','INDIA','USA']}

df = pd.DataFrame(d1)

print(df)

print('*'*30)

print(df.sort_index(ascending=False))

'''

Numpy - XII

Numpy

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