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Ans. a. Sales=pd.concat([Sales, Sales2], axis=1)
print(Sales)
b. Sales = Sales.T
c. print(Sales[2017])
d. print(Sales.loc[['Madhu','Ankit'], [2017,2018]])
e. print(Sales.loc['Shruti',2016])
f. Sales.loc["Sumeet"]=[196.2,37800,52000,78438,38852]
g. Sales.drop(columns=2014,inplace=True)
h. Sales.drop("Kinshuk",axis=0, inplace=True)
i. Sales=sales.rename({"Ankit":"Vivaan","Madhu":"Shailesh"}, axis="index")
j. Sales.loc["Shailesh",2018] = 100000
k. Sales.to_csv("salesFigures.csv",index=False,header=False)
l. SalesRetrieved=pd.read_csv("salesFigures.csv", header=None)
print(SalesRetrieved)
SalesRetrieved.columns = ['2014','2015','2016', '2017','2018']
SalesRetrieved.index=['Madhu', 'Kusum', 'Kinshuk', 'Ankit', 'Shruti','Sumeet']
print(SalesRetrieved)
7. Write the statement to install the python connector to connect MySQL i.e. pymysql.
Ans. pip install mysql-connector-python
OR
pip install pymysql
8. Explain the difference between pivot() and pivot_ table() function?
Ans. pivot() is a reshaping function in Pandas that reshapes a DataFrame based on unique values in a single column, creating
a new column for each unique value.
pivot_table() is a versatile function that not only reshapes data but also allows aggregation of values, handling
duplicate entries, and specifying multiple index/column levels for more complex reshaping and summarization tasks.
9. What is sqlalchemy?
Ans. SQLAlchemy is a library that facilitates the communication between Python programs and databases.
10. Can you sort a DataFrame with respect to multiple columns?
Ans. Yes. We can use the following statement to sort the DataFrame by multiple columns (say, A, B):
sortedDF = df.sort_values(by=['A', 'B'])
11. What are missing values? What are the strategies to handle them?
Ans. If a value corresponding to a column is not present, it is considered to be a missing value.
A missing value is denoted by NaN.
There are two most common strategies for handling missing values as mentioned below:
i. Drop the rows/columns having missing values,
ii. Fill or estimate the missing value
12. Define the following terms: Median, Standard Deviation and variance.
Ans. Median
The median is the middle value of a dataset, separating it into two equal halves. Function median() returns the median
from a set of numbers along the requested axis. It returns the median value that separates the higher half from the lower
half of a set of values.
84 Touchpad Informatics Practices-XII

