Program List Python DataFrame for Practical File

Program List Python DataFrame for Practical File provides 20 practical questions for CBSE Informatics Practices Class XII. If you missed the notes you can read from below given links:

Program List Python DataFrame on Dataframe Creation

The following section contains a Program List Python DataFrame based Dataframe Creation.

Write a program to:

1 Create an empty dataframe named as empty_df.

import pandas as pd

empty_df = pd.DataFrame()
print(empty_df)

2 Create a dataframe named as students using a list of names of 5 students.

import pandas as pd
students = ["Ram","Aman","Akash","Ramesh","Virat"]
students = pd.DataFrame(students,columns=["Name"])
print(students)

3 Write a program to create a dataframe players using a list of names and scores of the previous three matches.

Using Nested List

import pandas as pd 
data = [["Virat",55,66,31],["Rohit",88,66,43],["Samson",99,101,68]]
players = pd.DataFrame(data, columns = ["Name","Match-1","Match-2","Match-3"])
print(players)

Using Dictionary:

import pandas as pd 
data = {"Virat":[55,66,31],"Rohit":[88,66,43],"Samson":[99,101,68]}
players = pd.DataFrame(data,columns = ["Name","Match-1","Match-2","Match-3"])
print(players)

4 Write a program to create a dataframe salesman using the series sales_person which stored saleman names and quantity of sales of August.

import pandas as pd
sales_person = [["Ram",55],["Ajay",22],["Vijay",67],["Sachin",44]]
salesman = pd.DataFrame(sales_person,columns=["Name","Sales(August)"])
print(salesman)

5 Write a program to create a dataframe countries using a dictionary which stored country name, capitals and populations of the country.

import pandas as pd
country_data = {"Country Name":["India","Canada","Australia"],
                "Capital": ["New Delhi","Ottawa","Canberra"],
                "Population" : ["136 Cr","10 Cr","50 Cr"]
}
countries = pd.DataFrame(country_data)
print(countries)

6 Write a program to create a dataframe df_nda ndArray that stores letters and words starting from ‘g’ to ‘p’. (The first column stores letter and the second column stores the words starting with that letter.)

Program List Python DataFrame based on iterrows() and iteritems()

7 Iterate dataframe created in question no. 3 by its rows.

import pandas as pd 

data = [["Virat",55,66,31],["Rohit",88,66,43],["Samson",99,101,68]]
players = pd.DataFrame(data, columns = ["Name","Match-1","Match-2","Match-3"])

for index, row in players.iterrows():
    print(index, row.values)

8 Iterate dataframe created in question no. 4 by its columns.

import pandas as pd 

sales_person = [["Ram",55],["Ajay",22],["Vijay",67],["Sachin",44]]
salesman = pd.DataFrame(sales_person,columns=["Name","Sales(August)"])

for index, row in salesman.iterrows():
    print(index, row["Name"],row["Sales(August)"])

9 Print scores of previous two matches along with their names using iterrows function. (Use dataframe created in question 3)

import pandas as pd 

data = [["Virat",55,66,31],["Rohit",88,66,43],["Samson",99,101,68]]
players = pd.DataFrame(data, columns = ["Name","Match-1","Match-2","Match-3"])

for index, row in players.iterrows():
    print(index, row["Name"],row["Match-2"],row["Match-3"])

10 Print sales of salesman along with their index using iteritems(). (Use dataframe created in question 4)

import pandas as pd 

sales_person = [["Ram",55],["Ajay",22],["Vijay",67],["Sachin",44]]
salesman = pd.DataFrame(sales_person,columns=["Name","Sales(August)"])

for index, row in salesman.iterrows():
    print(index, row["Name"],row["Sales(August)"])

11 Display the alternate rows using iterrows() function.

12 Display the alternate columns using iteritems() function.

13 Make a total of score from the dataframe players and display their rank according the their scores.

import pandas as pd 

data = [["Virat",55,66,31],["Rohit",88,66,43],["Samson",99,101,68],["Pant",77,55,21]]
players = pd.DataFrame(data, columns = ["Name","Match-1","Match-2","Match-3"])

players['Total_score'] = players['Match-1'] + players['Match-2'] + players["Match-3"]
players['Rank'] = players['Total_score'].rank(ascending=0)
print(players)

Program List Python DataFrame based on insert rows and columns

14 Insert three new rows in dataframe students created by question 2.

import pandas as pd

students = ["Ram","Aman","Akash","Ramesh","Virat"]

students = pd.DataFrame(students,columns=["Name"])
print("---------- Original Dataframe --------------")
print(students)

values = ["Ajay","Vijay","Sanju"]
for val in values:
    temp = {"Name":val}
    students = students.append(temp,ignore_index=True)
print("----------- Updated DataFrame -------------")
print(students)

15 Insert two columns at the last of dataframe salesman named city and state using insert function.

import pandas as pd 

sales_person = [["Ram",55],["Ajay",22],["Vijay",67],["Sachin",44]]
salesman = pd.DataFrame(sales_person,columns=["Name","Sales(August)"])

salesman.insert(2,"City",["Mumbai","Baroda","Udaipur","Banglore"])
salesman.insert(3,"State",["Maharashtra","Gujarat","Rajasthan","Karnataka"])
print(salesman)

Some questions given in Assignments

Programs based on Select and Access data

Consider following data and write a program to do the following:

SNOBatsmanTestODIT20
1Virat Kohli354322451925
2Ajinkya Rehane257821651853
3Rohit Sharma228020801522
4Shikhar Dhawan215819571020
5Hardik Pandya18791856980

16 Print the batsman name along with runs scored in Test and T20 using column names and dot notation.

import pandas as pd 

# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}

data = pd.DataFrame(player_data)
# The following line is used to start the index from 1
data.index = data.index + 1

# ---------------------

print(data.Name)
print(data.Test)
print(data.T20)

17 Display the Batsman name along with runs scored in ODI using loc.

import pandas as pd 

# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}

data = pd.DataFrame(player_data)
# The following line is used to start the index from 1
data.index = data.index + 1

# ---------------------
print(data.loc[:,('Name','ODI')])

18 Display the batsman details who scored runs more than :

  1. More than 2000 in ODI
  2. Less than 2500 in Test
  3. More than 1500 in T20
import pandas as pd 

# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}

data = pd.DataFrame(player_data)
# The following line is used to start the index from 1
data.index = data.index + 1

# runs more than 2500 in ODI
print("---- Runs greater than 2500 in ODI ---------")
print(data.loc[data['ODI']>2500, ['Name']])

# Less than 2500 runs in test
print("---- Runs less than 2500 in Test ---------")
print(data.loc[data['Test']<2500, ['Name']])

# More than 1500 runs in T20
print("---- Runs more than 1500 in T20 ---------")
print(data.loc[data['T20']>1500, ['Name']])

19 Display the columns using column index number like 0, 2, 4.

import pandas as pd 

# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}

data = pd.DataFrame(player_data)
# The following line is used to start the index from 1
data.index = data.index + 1

# =======================
print(data[data.columns[0]])
print(data[data.columns[2]])

20 Display the alternated rows using at() function.

import pandas as pd 

# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}

data = pd.DataFrame(player_data)
# The following line is used to start the index from 1
data.index = data.index + 1

# ==============
print(data.at[1,])

21 Reindex the dataframe created above with batsman name and delete data of Hardik Pandya and Shikhar Dhawan by their index from original dataframe.

import pandas as pd 
# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}
data = pd.DataFrame(player_data)
# The following line is used to start the index from 1
data.index = data.index + 1
# ----------------------
data = data.set_index('Name')
print(data)
# Now deleting records
print("Records after Deleting the values:")
data = data.drop(['Shikhar Dhawan','Hardik Pandya'])
print(data)

22 Insert 2 rows in the dataframe and delete rows whose index is 1 and 4.

import pandas as pd 
# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}

data = pd.DataFrame(player_data)
# ----------------------
values = {'Name':['Rishabh Pant','Shreyas Iyer'],'Test':[1500,1459],'ODI':[1980,1342],'T20':[2300,1988]}
data = data.append(pd.DataFrame(values), ignore_index=True)
print(data)

# -----
print("Data after deleting index 1 and 4")
data = data.drop([1,4])
print(data)

23 Delete a column Test, add one more column at last (next to T20 column), make total of ODI and T20 runs in that column.

import pandas as pd 
# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}
data = pd.DataFrame(player_data)
# The following line is used to start the index from 1
data.index = data.index + 1
# ----------------------
data = data.drop('Test', axis = 1)
print(data)
# ---------------
total = data['ODI'] + data["T20"]
data['Total'] = total
print(data)

24 Delete columns using T20 and total using columns parameter in drop() function.

import pandas as pd 

# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}

data = pd.DataFrame(player_data)
# The following line is used to start the index from 1
data.index = data.index + 1
# ---------------
total = data['ODI'] + data["T20"]
data['Total'] = total

data = data.drop(['T20','Total'], axis = 1)
print(data)

25 Rename column T20 with “T20I Runs”.

import pandas as pd 

# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}

data = pd.DataFrame(player_data)
# The following line is used to start the index from 1
data.index = data.index + 1

# ----------------------
data.rename(columns={'T20':'T20I runs'}, inplace = True)
print(data)

26 Rename all the columns of dataframe with your choice of column names.

import pandas as pd 

# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}

data = pd.DataFrame(player_data)
# The following line is used to start the index from 1
data.index = data.index + 1

# ----------------------
data.rename(columns={'T20':'T20I runs','Name':'Player Name','Test':'Test Runs','ODI':'ODI Runs'}, inplace = True)
print(data)

27 Rename the index with prefix IND and number like 001 and So on.

import pandas as pd 

# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}

data = pd.DataFrame(player_data)
# The following line is used to start the index from 1
data.index = data.index + 1

# ----------------------
index = pd.Index(["001","002","003","004","005"])
data = pd.DataFrame(player_data,index)
data = data.rename_axis('IND')
print(data)

28 Display the first two rows and last two rows.

import pandas as pd 

# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}

data = pd.DataFrame(player_data)
# The following line is used to start the index from 1
data.index = data.index + 1

# ----------------------
print(data.head(2))
print(data.tail(2))

29 Count the total number of rows and columns of the dataframe.

import pandas as pd 

# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}

data = pd.DataFrame(player_data)
# The following line is used to start the index from 1
data.index = data.index + 1

# ----------------------
total_rows = len(data.axes[0])
total_col = len(data.axes[1])

print("Total Rows: " + str(total_rows))
print("Total Columns: " + str(total_col))

30 Print the dataframe without headers. Go for the multiple options.

import pandas as pd 

# Creating the Data
player_data = {"Name":["Virat Kohli","Ajinkya Rahane","Rohit Sharma","Shikhar Dhawan","Hardik Pandya"],
                "Test" : [3543,2578,2280,2158,1879],
                "ODI" : [2245,2165,2080,1957,1856],
                "T20" : [1925,1853,1522,1020,980]
}

data = pd.DataFrame(player_data)
# The following line is used to start the index from 1
data.index = data.index + 1

# ----------------------
print(data.to_csv(header=None,index=False))

See this also: Assignment

Click here for more practice questions.

I thank my student Neel Patel for his contribution in this article.

If you have any other code or solution for any question, write in comment section. So your friends will learn about more methods and code.

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