Pandas: Data Handling Techniques

Question 1

Panda stands for ?

Answer 1

Python Data Analysis Library

Question 2

How to install Pandas

Answer 2

pip install pandas

Question 3

How to import Pandas module ?

Answer 3

import pandas as pd

Question 4

How to import csv file ?

Answer 4

dataFrame=pd.read_csv('Book.csv')

Question 5

How to get first n rows ?

Answer 5

head=dataFrame.head(10)

Question 6

How to get last n rows ?

Answer 6

tail=dataFrame.tail(10)

Question 7

How to get all row and column values in the data frame ?

Answer 7

We have to use shape property.
~~~
row,column=dataFrame.shape
~~~

Question 8

How to save specific rows in available ?

Answer 8

It will save to row5 to row 10 data in a variable.
~~~
speciFicRows=dataFrame[5:10]
~~~

Question 9

How to get all rows from n row to last ?

Answer 9

speciFicRows=dataFrame[5:]

Question 10

How to get only specific column in a variable

Answer 10

column1=dataFrame.Income

Question 11

How to get multiple columns in a variable ?

Answer 11

column2=dataFrame[['Age','Income']]

Question 12

How to get specific row and columns in variable ?

Answer 12

x=dataFrame.iloc[0:4,0:3]

Question 13

Which Panda method is label based ?

Answer 13

df.loc[]

Question 14

Which Pandas method is integer index value based ?

Answer 14

df.iocl[]

Question 15

How to get the minimum and maximum value of columns ?

Answer 15

df.Age.max()
df.Age.min()

Question 16

How to get mean of column Numerical values ?

Answer 16

df.Age.mean()

Question 17

How to get standard deviation of numeric values in colum ?

Answer 17

df.Age.std()

Question 18

How to use describe method to describe dataframe?

Answer 18

include =['object', 'float', 'int']
percentile=[.5, .10, .20, .40, .60, .80]
df.describe(percentiles = percentile,include = include)