Pandas Interview Questions – Part 1
Pandas Interview Questions
We will have 10-15 questions in each post with solutions and you can complete the series in 4-5 posts. Go through each question and practice on your system
I this part of Pandas Interview Questions, we will cover the very basics.
Q1. What is Pandas ?
A1. Pandas is a powerful, flexible, open source and easy to use data analysis and manipulation tool. It aims to be the fundamental building block for data analysis , data manipulation tasks.
Q2. What is python pandas used for ?
A2. Pandas is a open source library of python programming language. Which is mostly use for Data manipulation and analysis.
Microsoft Word – Final_Pandas_Neha.docx
Q3. Write Steps to install Pandas on Windows.
A2. These are the following steps :
1. The initial step would be to download Python on windows 2. Run the Python executable installer
3. Install pip on Windows
4. Install Pandas in Python using pip
“pip install pandas”
Microsoft Word – Final_Pandas_Neha.docx
Q4. What are the key features of pandas library ?
A3. These are various features in pandas library :
- Memory Efficient
- Reshaping
- Merge and join
- Time Series
- Data Alignment
Microsoft Word – Final_Pandas_Neha.docx
Q5. What is pandas dataframe ?
A5. Pandas dataframe is a 2- dimensional heterogeneous data structure with labeled axes (rows and columns). Pandas dataframe consists of three principle components Data, rows and columns.
Microsoft Word – Final_Pandas_Neha.docx
Q6. How to Import Pandas Library and also check the version of Library.
A6.
Microsoft Word – Final_Pandas_Neha.docx
# Load the Pandas library with alias pd
import pandas as pd
print(pd.__version__)
Microsoft Word – Final_Pandas_Neha.docx
Q7. How to read the different – different format files using pandas??
A7.
Microsoft Word – Final_Pandas_Neha.docx
# Reading the Comma Separated file pd.read_csv( ‘filename.csv’)
# Reading the tab separated file pd.read_table (‘filename.tsv’)
# Reading the Excel File using Pandas
Microsoft Word – Final_Pandas_Neha.docx
Pd.read_excel( ‘filename.xlsx’)
# Reading the Html file using pandas Pd.read_html(‘filename.html’)
Microsoft Word – Final_Pandas_Neha.docx
Q8. How to create a Series from a numpy array, list and dictionary?
A8. Series : Pandas Series is nothing but a Single Column of the Excel Sheet or we can say that Series is a 1D array capable of holding the data of any type(str, int, float etc)
#Load the numpy library with alias np
import numpy as np
# Creating the List
mylist = [1,2,3,4,5]
# Converting the List into Series
Ser1= pd.Series ( Mylist)
print ( Ser1 )
# Series Creation using Numpy array
# importing numpy library
import numpy as np
# data
arr= np.arange(10)
# array to Series Conversion
Ser2= pd.Series(arr)
print( Ser2)
# Series using Dictionary
Mydic = { 1: ‘Monday’, 2: ‘Tuesday’,3: ‘Wednesday’, 4: ‘Thursday’, 5: ‘Friday’, 6 : ‘Saturday’}
Ser3= pd.Series(Mydic)
print(Ser3)
How to make DataFrame using 2 Series?
# Input data
mylist = [1,2,3,4,5,6,7]
# list to Series conversion Ser1= pd.Series (mylist)
Mydic= { 0: ‘days’,1: ‘Monday’, 2: ‘Tuesday’,3: ‘Wednesday’, 4: ‘Thursday’, 5: ‘Friday’, 6 : ‘Saturday’}
# dict to series conversion Ser2= pd.Series(Mydic)
# Concatenation of both series
df = pd.concat ( [Ser1, Ser2 ],axis=1) print(df)
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Important Resources to crack interviews (Mostly Free)
There are a few things that might be very useful for your preparation
The Data Monk Youtube channel – Here you will get only those videos that are asked in interviews with Data Analysts, Data Scientists, Machine Learning Engineers, Business Intelligence Engineers, Analytics managers, etc.
Go through the watchlist which makes you uncomfortable:-
All the list of 200 videos
Complete Python Playlist for Data Science
Company-wise Data Science Interview Questions – Must Watch
All important Machine Learning Algorithm with code in Python
Complete Python Numpy Playlist
Complete Python Pandas Playlist
SQL Complete Playlist
Case Study and Guesstimates Complete Playlist
Complete Playlist of Statistics
Keep Learning !!
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