Question: Use appropriate data cleaning techniques and methods in Pandas to convert the raw file into clean data structure and answer the following questions. Your
Use appropriate data cleaning techniques and methods in Pandas to convert the raw file into clean data structure ” and answer the following questions. Your answers should be accurate. All cleaning and manipulation should be done in Python only. Be careful for subtotals in the data to avoid double counting.
Paste your cleaning code of PYTHON here ,
Write the full code that lead to the answer of each of the following questions in the single cell below each question.
Q2) What is the grand total number of wickets taken by all the players ?
Q3) What is the total number of runs made in each match?
Q4) Show the average number of runs in each Match using a bar graph.?
Q5) Import the tips dataset and complete the parts below ,
5a) Find out the correlation between total bill, tip and size column using appropriate data frame method.
5b) Show the result of question 4 in a form of a seaborn package heatmap. (Q5b references question 4 asking for a heatmap. The question should read: "Show the result of question 5a in a form of a seaborn package heatmap. ")
PYTHON Data Cleaning and Basic Plotting
Player Code | Player Name | Match Number | Number of Wickets Taken | Number of Runs | |
45234 | Maud Nicholson | M1 | 2 | 82 | |
M3 | 3 | 71 | |||
M5 | 0 | 36 | |||
M6 | 1 | 76 | |||
Total Runs | 14 | ||||
4578 | Logan Thomas | M1 | 0 | 4 | |
M3 | 1 | 38 | |||
Player Runs Total | 100 | ||||
4545 | Avaya Burris | M1 | 0 | 57 | |
M3 | 0 | 76 | |||
M5 | 0 | 28 | |||
Player Runs Total | 34 | ||||
4456 | Marlie Stacey | M1 | 0 | 87 | |
M3 | 4 | 58 | |||
M5 | 0 | 100 | |||
Player Runs Total | 12 | ||||
4545 | Onur Bateman | M1 | 0 | 21 |
Step by Step Solution
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PYTHON Data Cleaning and Basic Plotting import pandas as pd read the raw data df pdreadcsvrawdatacsv drop unnecessary columns dfdropPlayer Code axis1 inplaceTrue create a pivot table to aggregate the ... View full answer
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