Solved Assignment Create Dataframe IP class 12

 

Solved Assignment Create Dataframe IP class 12 provides important QnA for creating dataframe topic. Read them and understand them. 

Solved Assignment Create Dataframe IP class 12

Answer the following questions for Solved Assignment Create Dataframe IP class 12. 

  • Define Dataframes.
  • What are the characteristics of Dataframes?
  • Which packages are needed to be imported to create dataframes? Explain with syntax and example.
  • How to create and display an empty dataframe?

For the answer to the above questions follow this link for Solved Assignment Create Dataframe IP class 12. 

The next questions for Solved Assignment Create Dataframe IP class 12 are based on some coding practices: 

  • Create a dataframe with these data and display with single column: [33,55,66,39,45]
import pandas as pd
def df_SingleColumn():
l = [33,55,66,39,45]
sum1=0
df = pd.DataFrame(l)
sum1=df.sum()
print("Sum of given numbers:", sum1.to_string(index=False))
df_SingleColumn()
  • Create a dataframe with the above data (Q-5) and display the sum of the given numbers:
  import pandas as pd
def df_SingleColumn():
l = [33,55,66,39,45]
sum1=0
df = pd.DataFrame(l)
sum1=df.sum()
print("Sum of given numbers:", sum1.to_string(index=False))
df_SingleColumn()
  • What will be the output of following code:
import pandas as pd
def df_data():
df1=pd.DataFrame([22,56,78])
df2=pd.DataFrame([[11,43,67]])
print(df1)
print(df2)
df_data()
Answer:

 

    0
0 22
1 56
2 78
0 1 2
0 11 43 67

In this code two data frames created. In the first dataframe there is a single-column list is which creates a single column. Similarly in the second dataframe, multiple columns created using double square brackets.

 
Watch the complete video lesson

 
  • Create a dataframe named booking with the following data:
 TCode  Name  Tickets  Amount
 T0001  Anuj Maheta  5  1355
 T0002  Sandeep Oza  2  1169
 T0003  Manvi Sharma  6  1988
import pandas as pd
def df_booking():
data = [['T0001','Anuj Maheta',5,1355],
['T0002','Sandeep Oza',2,1169,],
['T0003','Manavi Sharma',6,1988]]
booking=pd.DataFrame(data,columns=['Tcode','Name','Tickets','Amount'])
print(booking.to_string(index=False))
df_booking()
  • Create a dataframe furniture shown in the following table:
 Item  Material  Colour  Price
 Sofa  Wooden  Maroon  25000
 Dining Table  Plywood Yellow  20000
 Chair  Plastic  Red  1500
 Sofa  Stainless Steel  Silver  55000
 Chair  Wooden   Light Blue  2500
 Dining Table  Aluminum  Golden  65000

a) Display the details of the chair and sofa.

b) Display furniture details which price is more than 25000.
c) Display the furniture details price under 10000.
d) Display alternative rows. 
 
Answer:
Creating Dataframe:
import pandas as pd
def df_furniture():
data = [['Sofa','Wooden','Maroon',25000],
['Dining Table','Plywood','Yellow',20000],
['Chair','Plastic', 'Red',1500],
['Sofa','Stainless Steel', 'Silver',55000],
['Chair','Wooden', 'Light Blue',2500],
['Dining Table','Aluminum', 'Golden',65000],]
furniture=pd.DataFrame(data,columns=['Item','Material','Colour','Price'])
print(furniture.to_string(index=False))
df_furniture()
a) print(furniture[furniture[‘Item’]==’Sofa’],”n”,furniture[furniture[‘Item’]==’Chair’]) 
b) print(furniture[furniture[‘Price’]>25000])
c) print(furniture[furniture[‘Price’]<10000])
d) print(furniture.iloc[::2])
 
  • Create a dataframe using the 2D dictionary to store the following records:
 House  Activity1  Activity2  Activity3
 Blue House  98  85  88
 Red House  87  76  80
 Green House  59  67  91
 Yellow House  78  99  55

Answer:

import pandas as pd
def df_CCA():
data = {'House':['Blue House','Red House','Green House','Yellow House'],
'Activity1':[98,87,59,78],
'Activity2':[85,76,67,99],
'Activity3':[88,80,91,55]}
furniture=pd.DataFrame(data)
print(furniture.to_string(index=False))
df_CCA()
  • Create a dataframe using the 2d dictionary with values as dictionary objects which store data of CCA activities for two terms:
   Red  Green  Blue  Yellow
 Term1  200  350  400  380
 Term2  189  250  375  300
import pandas as pd
def df_CCA():
r={'Term1':200,'Term2':189}
g={'Term1':350,'Term2':250}
b={'Term1':400,'Term2':400}
y={'Term1':380,'Term2':300}
c={'Red':r,'Green':g,'Blue':b,'Yellow':y}
df=pd.DataFrame(c)
print(df)
df_CCA()
  • Create a dataframe using the following matrix by ndarray, assign row, and column labels like MS excel.
   A  B  C
 1  98  56  87
 2  32  76  65
 3  55  99  88
import pandas as pd
import numpy as np
def df_ndArray():
nda=np.array([[98,56,97],[32,76,65],[55,99,88]])
df=pd.DataFrame(nda,columns=['A','B','C'],index=[1,2,3])
print(df)
df_ndArray()

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