Question Aapython please for the commented steps. ✓OsOsExploring and Visualizing The DataExploring 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 matplotlib23 import matplotlib.pyplot as plt4 %matplotlib inline.56 #### the statement below ask matplotlib to use the 'ggplot' style7 #### you should consider using that8plt.style.use('ggplot')1 #### Complete your code below2 #### create a histogram `hist()` over the column `df [ 'W']`34 #### adding elements to your visualization to increase the readability5 #### you should always have title and axis name (s) in your visualization6 #### name your x-axis label as `Wins`789 #### name your visualization title as `Distribution of Wins`101112 #### show your visualization131 #### We can also check the descriptive stats of `df [ 'W']` using `.describe()2

1 # create histogram2 plt.hist(df['W'], bins=10)34 # add x-axis label5 plt.xlabel('Wins')67 # add…

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

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

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