Exploring and Visualizing The Data Exploring your data using different types of visualizations is always a good practice when doing EDA. You'll start by plotting a histogram of the target column (w) so you can see the distribution of wins. [79] 1 #importing matplotlib
Exploring and Visualizing The Data Exploring your data using different types of visualizations is always a good practice when doing EDA. You'll start by plotting a histogram of the target column (w) so you can see the distribution of wins. [79] 1 #importing matplotlib
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Question Aa
python please for the commented steps.
![✓
Os
Os
Exploring and Visualizing The Data
Exploring your data using different types of visualizations is always a good practice when doing EDA.
You'll start by plotting a histogram of the target column (w) so you can see the distribution of wins.
[79]
[ ]
[]
1 #importing matplotlib
2
3 import matplotlib.pyplot as plt
4 %matplotlib inline.
5
6 #### the statement below ask matplotlib to use the 'ggplot' style
7 #### you should consider using that
8
plt.style.use('ggplot')
1 #### Complete your code below
2 #### create a histogram `hist()` over the column `df [ 'W']`
3
4 #### adding elements to your visualization to increase the readability
5 #### you should always have title and axis name (s) in your visualization
6 #### name your x-axis label as `Wins`
7
8
9 #### name your visualization title as `Distribution of Wins`
10
11
12 #### show your visualization
13
1 #### We can also check the descriptive stats of `df [ 'W']` using `.describe()
2](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F7c25bf90-34a6-4bc8-9056-4d36c71f5aff%2Ffed29cdc-f9da-471b-bd42-4430fb8cc308%2Fhr9mny_processed.png&w=3840&q=75)
Transcribed Image Text:✓
Os
Os
Exploring and Visualizing The Data
Exploring your data using different types of visualizations is always a good practice when doing EDA.
You'll start by plotting a histogram of the target column (w) so you can see the distribution of wins.
[79]
[ ]
[]
1 #importing matplotlib
2
3 import matplotlib.pyplot as plt
4 %matplotlib inline.
5
6 #### the statement below ask matplotlib to use the 'ggplot' style
7 #### you should consider using that
8
plt.style.use('ggplot')
1 #### Complete your code below
2 #### create a histogram `hist()` over the column `df [ 'W']`
3
4 #### adding elements to your visualization to increase the readability
5 #### you should always have title and axis name (s) in your visualization
6 #### name your x-axis label as `Wins`
7
8
9 #### name your visualization title as `Distribution of Wins`
10
11
12 #### show your visualization
13
1 #### We can also check the descriptive stats of `df [ 'W']` using `.describe()
2
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