Real Interview Questions given by a Data Analytics Company 🏢#interview #dataanlysis #python

Download Source Code of this project (Rs.39) - https://rzp.io/l/interviewQA Purchase - Python Data Science Self Study Notes & All Projects Source Codes - https://rzp.io/l/dslnotes239 Download Dataset File - https://datasciencelovers.graphy.com/products/Dataset--Data-Analyst-Interview-QA-64ef307e0c9e221bb89b1fb9?dgps_s=pbl&dgps_u=c&dgps_uid=64cb5694e4b000cf748a30c2&dgps_t=cp_m Enrol in our Udemy courses : 1. Python Data Analytics Projects - https://www.udemy.com/course/bigdata-analysis-python/?referralCode=F75B5F25D61BD4E5F161 2. Python For Data Science - https://www.udemy.com/course/python-for-data-science-real-time-exercises/?referralCode=9C91F0B8A3F0EB67FE67 3. Numpy For Data Science - https://www.udemy.com/course/python-numpy-exercises/?referralCode=FF9EDB87794FED46CBDF Download Free Core Python Notes - https://datasciencelovers.graphy.com/products/Core-Python-Notes-64d116f7c7a9985f7b99a5bf?dgps_s=dsh&dgps_u=c&dgps_uid=64cb5694e4b000cf748a30c2&dgps_t=cp_m Download - Python Pandas Notes ( Rs.50 ) - http://bit.ly/3KxMpgA ---------------------------------------------------------- Watch demo of Self Study Material - https://youtu.be/LoFpsODdkuo Outside India, PayPal for Self Study Material ($5) - [email protected] ---------------------------------------------------------- Contact Mail Id : [email protected] ---------------------------------------------------------- In this video, we covered the Technical Interview round for the position of Data Analyst in a company. Questions and data provided by the company, we solved the questions with Python (Pandas) in Jupyter Notebook. The commands that are used in the video - # head( ) # unique ( ) # nunique ( ) # value_counts ( ) # dtype # replace ( ) # "inplace = True" # astype ( ) # Filtering # Creating a new Column # copy ( ) # insert ( ) # Creating a new Dataframe # Concatenation (dataframes) # type ( ) # Line Chart # figsize ( ) # Pivot Table # Groupby # count ( ) # Merge ---------------------------------------- Question 1 - Load the dataset into a pandas dataframe. Name the variable as “survey”. Question 2 - How many samples were collected on each day? Question 3 - What proportion of the total respondents were aged less than 45? Question 4 - Create a new column in the dataframe “age_group”. This column should contain the age group the respondent belongs to. The age groups are 18-25, 25-40, 40-55 and 55+. The dataframe should look like this after the column creation. Question 5 - How many samples were collected for each age-group? Which age-group had the most samples? Question 6 - What proportion of the respondents had opted for the RJD party in both the Vote_Now and the Past_Vote questions? Question 7 - For each day of sample collection, determine the proportion of respondents who were fully satisfied with the performance of the CM. So if there were a total of 1000 samples on day 1 and 300 out of those said they were fully satisfied, then our answer for that day would be 0.3. Question 8 - In a similar fashion create a day-wise proportion of respondents that opted fully dissatisfied with their MLA. Create a line plot of the result with date on x-axis and proportions on the y-axis. Question 9 - Create a pivot-table (or crosstab) with index as Past_Vote, Column as Vote_Now and cell values as the count of samples. Answer - survey.pivot_table(index = 'Past_Vote', columns = 'Vote_Now', values = 'response_id', aggfunc = 'count') Question 10 - Repeat the above question with the cell values as the sum of “weight”. Question 11 - Create a dataframe by performing a group by over age_group and calculate the count of total samples under each age_group. Question 12 - Create a dataframe by performing a group by over age_group and finding the count of total samples for each age_group that opted for the JD(U) party in Vote_Now. Question 13 - Join/Merge the two dataframes from questions 12 and 11 with the common column as age_group. ---------------------------- You must check our other videos : Project 8 - https://youtu.be/b7Kd0fLwgO4 Project 7 - https://youtu.be/AO5uhxa1R84 Project 6 - https://youtu.be/e1zKFSrKeLs Project 5 - https://youtu.be/q-Omt6LgRLc Project 4 - https://youtu.be/89eYAAPyRfo Project 3 - https://youtu.be/GyUbo45mVSE Project 2 - https://www.youtube.com/watch?v=fhiUl7f5DnI Project 1 - https://youtu.be/4hYOkHijtNw #python #dataanalytics #datascience #interview