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23. Sushila has created a DataFrame with the help of the following code: [2022]
import pandas
EMP={'EMPID': ['E01', 'E02', 'E03', 'E04', 'E05'],
'EMPNAME' : ['KISHORI','PRIYA', 'DAMODAR', 'REEMA', 'MANOJ'],
'EMP_SALARY': [67000,34000,68000,90000,43000]
}
df=pandas.DataFrame(EMP, index=['001','002', '003','004','005])
print(df.loc[0:3,:])
and she wants to get the following output:
EMPID EMPNAME EMP_SALARY
001 E01 KISHORI 67000
002 E02 PRIYA 34000
003 E03 DAMODAR 68000
Help her to correct the code.
a. print(df.iloc['001':'003',:]) b. print(df.loc['001': '003',:])
c. print(EMP[loc[0:3,:]]) d. print(df.loc['001' :'004',:])
Ans. b. print(df.loc['001': '003',:])
NCERT Exercise Solutions
1. What is a DataFrame and how is it different from a 2-D array?
Ans. A Pandas DataFrame is a two-dimensional tabular structure that can accommodate objects of various types. while a NumPy
2D array is a homogeneous, fixed-size array with numerical elements, lacking labeled axes and advanced data manipulation
functionalities.
2. How are DataFrames related to Series?
Ans. A DataFrame in Pandas is a two-dimensional, tabular data structure made up of multiple Series. A Series, on the other
hand, is a one-dimensional labelled array that can hold any type of data. Each column in a DataFrame is essentially a Series,
with a common index. As a result, a DataFrame can be thought of as a collection of Series with the same index.
3. What do you understand by the size of a DataFrame?
Ans. The size of a DataFrame in Pandas refers to the total number of elements it contains, which is calculated as the product of
the number of rows and columns.
4. Create the following DataFrame Sales containing year wise sales figures for five sales persons in INR. Use the years as
column labels, and sales person names as row labels.
2014 2015 2016 2017
Madhu 100.5 12000 20000 50000
Kusum 150.8 18000 50000 60000
Kinshuk 200.9 22000 70000 70000
Ankit 30000 30000 100000 80000
Shruti 40000 45000 125000 90000
Ans. import pandas as pd
dict1 = {2014:[100.5,150.8,200.9,30000,4000],
2015:[12000,18000,22000,30000,45000],
2016:[20000,50000,70000,10000,125000],
2017:[50000,60000,70000,80000,90000]}
Sales=pd.DataFrame(dict1,
index=['Madhu',"Kusum","Kinshuk","Ankit","Shruti"])
print(Sales)
82 Touchpad Informatics Practices-XII

