Skip to content

Latest commit

 

History

History
46 lines (42 loc) · 2.78 KB

exercises.md

File metadata and controls

46 lines (42 loc) · 2.78 KB
Raw

Parliment Data Set

  • For top ten parties compute the following metrics for the year 2009

    • Total number of contestants
    • Total of number of winning seats
    • Avg. %of votes

  • Identify top ten candidates with highest %margin of votes for the year 2009

  • Identify year wise percentage of male and female candidates?

ODI Batting

  • Create a new column by binning the Runs column using the following ranges and plot the frequency count of ranges
    • 0-25, 26-50, 51-75, 76-100, 100+
  • Consider the top ten players by total runs and compute and visualize the number of centuries across years (use facet_grid or facet_wrap)
  • Compute total number of breaks taken by each player and identify top five players. (Note: A break is considered, if a player has not played any match in a year)
  • For top ten players (based on total runs) compute the following metrics
    • Total runs
    • Total centuries
    • Total Fifties
    • Total Ducks
    • Total experience in terms of number of years they have played
  • Calculate total number of runs scored by each player. The output should be a dictionary. The player names should be the keys and total runs should be values
  • Convert Match Date column to datetime column and compute the following new columns
    • Year, month
  • Identify in which year sachin has played most number of matches
  • Identify in which year sachin has scored most number of runs
  • Identify in which year sachin has scored most number of centuries

Tweets (#narendramodi)

  • Monthwise total number of tweets in a bar chart
  • Create a new column for quarter and compute quarter wise total number of tweets from each quarter
  • Create a new column to identify the number of hashtags and compute device-wise average number of retweets
  • Create a stacked bar chart to visualize month-wise total number of tweets from each device
  • Create a scatter plot with the following details
    • X axis contains number of retweets
    • Y axis contains number of likes
    • Color represents device from which it was tweeted
  • Create a heat map or tile plot to visualize number of tweets by day of month and month of the year

Bank Campaign data set

  • Identify unique job categories
  • Identify min, max, median based on balance column and also plot a box plot to see if there are any outliers
  • Create a new column based on Balance column. The values in new column should be "group-1" if balance is more than 15000 else "group-2"
  • Identify the percentage of students who are targetted for campaign
  • Using apply function create a new column called "response_numeric". In which values should be 0 if y is "no" and values should be 1 if y is "yes"
  • Compute average response by each job category
  • Create pivot table in which rows represents job category, columns represents marital status and values represents total number of campaigns