DATAFRAME IMP QUESTIONS

 

QUE. Consider the following CORONA DataFrame and answer the questions given below:

ID	State	Cases
100	Delhi	3000
110	Mumbai	4000
120	Chennai	5000
130	Surat	4500

Create the above dictionary and DataFrame with given data and perform the following operations:

(a) Write code to add a new column named 'Recovery' using the Series method. This column should store the number of patients recovered in each state. (Assume appropriate values)

(b) Add a new column named 'Deaths' using the assign() method to store the number of deaths in each state. (Assume values)

(c) Add a new row using loc[] to store details of another state. (Assume values)

(d) Add a new column named 'Percentage' using the insert() method. This column should store the percentage of recovery in each state and must be added as the fourth column of the DataFrame. (Assume values)

(e) Delete the column 'Percentage' using the del command.

(f) Delete the column 'Deaths' using the pop() method.

(g) Insert a new row using iloc[] method at the first position (i.e., index 0). (Assume values)

(h) Temporarily delete the columns 'Cases' and 'State' from the DataFrame without modifying the original.

 Sol:

  import pandas as pd

# Creating the dictionary

data = {

    'ID': [100, 110, 120, 130],

    'State': ['Delhi', 'Mumbai', 'Chennai', 'Surat'],

    'Cases': [3000, 4000, 5000, 4500]

}

CORONA = pd.DataFrame(data)

 (a) Add a new column 'Recovery' using the Series method

recovery = pd.Series([2800, 3700, 4700, 4200])

CORONA['Recovery'] = recovery

(b) Add a new column 'Deaths' using the assign() method

CORONA['Deaths'] = [150, 180, 200, 250, 190]

(c) Add a new row using loc[] (e.g., for Bangalore)

CORONA.loc[4] = [140, 'Bangalore', 4800, 4600, 190]

(d) Add a column 'Percentage' using the insert() method (at index 3)

percentage = [93.3, 92.5, 94.0, 93.3, 95.8]

CORONA.insert(3, 'Percentage', percentage)

(e) Delete the column 'Percentage' using del

del CORONA['Percentage']

(f) Delete the column 'Deaths' using pop() method

CORONA.pop('Deaths')

(g) Insert a new row using iloc[] at the 1st position

new_row = [150, 'Hyderabad', 4200, 4000]

# Insert at position 0

CORONA.loc[-1] = new_row        # Add the new row with a temporary index

CORONA.index = CORONA.index + 1 # Shift all indexes by 1

CORONA = CORONA.sort_index()    # Sort by index to reorder

(h) Temporarily delete 'Cases' and 'State' (without modifying original)

temp_df = CORONA.drop(['Cases', 'State'], axis=1)

print(temp_df)

QUE 2:

Consider the following EMPLOYEE DataFrame and answer the questions given below:

EmpID	Name	Department	Salary
101	Amit	HR	40000
102	Neha	IT	55000
103	Raj	Finance	50000
104	Priya	IT	60000

Create the above dictionary and DataFrame with given data and perform the following operations:

(a) Add a new column named Bonus using the Series method. (Assume values for each employee)

(b) Add a new column named Tax using the assign() method. (Assume values for each employee)

(c) Add a new row using loc[] to store details of another employee. (Assume values)

(d) Delete the column NetSalary using the del command.

(e) Delete the column Tax using the pop() method.

 Sol:

import pandas as pd

# Creating the dictionary

data = {

    'EmpID': [101, 102, 103, 104],

    'Name': ['Amit', 'Neha', 'Raj', 'Priya'],

    'Department': ['HR', 'IT', 'Finance', 'IT'],

    'Salary': [40000, 55000, 50000, 60000]

}

EMPLOYEE = pd.DataFrame(data)

print("Initial DataFrame:\n", EMPLOYEE)

 

# (a) Add a new column 'Bonus' using the Series method

bonus = pd.Series([5000, 7000, 6500, 8000])

EMPLOYEE['Bonus'] = bonus

print("\nAfter adding Bonus column:\n", EMPLOYEE)

 

# (b) Add a new column 'Tax' using assign() method

EMPLOYEE = EMPLOYEE.assign(Tax=[4000, 5500, 5000, 6000])

print("\nAfter adding Tax column:\n", EMPLOYEE)

 

# (c) Add a new row using loc[] (for example, for employee Sanya)

EMPLOYEE.loc[4] = [105, 'Sanya', 'HR', 45000, 6000, 4500]

print("\nAfter adding a new row using loc[]:\n", EMPLOYEE)

 

# (d) Delete the column 'NetSalary' using del

del EMPLOYEE['NetSalary']

print("\nAfter deleting NetSalary column:\n", EMPLOYEE)

 

# (e) Delete the column 'Tax' using pop() method

EMPLOYEE.pop('Tax')

print("\nAfter deleting Tax column:\n", EMPLOYEE)