I'll explore these tables and select the important columns for me and start my analysis journey.
Questions:
1- Is there any relationship between the height & the weight of the players?
2- Who is the best finisher and who is the fastest player?
3- Is there any relationship between the finishing score & the penalties of the players?
4- What is the preferred foot for the players?
5- What is the relation between the player's age and his overall rating?
6- What is the percentage of the attack & defense work rate?
7- What is the distribution of players' age, putting the preferred foot in consideration?
8- Which league has the maximum & minimum goals?
9- Which team has scored the maximum goals on his land during our timeframe?
10 - What teams improved their defense over the time period in the Switzerland Super League?
Solution:
I used Pandas & Numpy to make a data wrangling process to the dataset first and come up with about 20 points to be cleaned and put in a cleaning summary.
Then started my exploratory analysis to find out some statistics about the numerical columns of the data.
And finally, I started answering the pre-specified questions and used Seaborn & Matplotlip to plot charts that convey my messages.
Insights & Conclusions:
We have a player who is 49 years old.
The shortest player is 157.48 cm.
The weight range between 117 & 243 lbs.
Height, Weight, and Age are forming a normal distribution.
Most of the player's ages are between 25 & 30.
The correlation between weight & height is positive and strong.
We can neglect the relationship between age vs. weight & height., it is really weak but positive.
It is clear that there is a positive trend between the height & weight of the players with a correlation coefficient of 0.77.
Lionel Messi is the best finisher with a score of 97.
David Odonkor is the fastest player with a score of 97.
There is a strong positive relationship between finishing & penalties of the players.
There are a few players who have very low finishing scores and significant-high penalities scores and vice versa.
76% of the players prefer the right foot.
There may be high demand for left-foot players.
Players with an overall rating of +90 are falling between 22 & 35 years.
I can see two trends above 70 ratings, increasing one starting from age 16 to 28, then decreasing one from 28 to 44. The medium defense & attacking work rate is the most percentage.
High work rate has bigger percentage than low work rate in attack & defense.
High attacking work rate is more than the high defensive work rate.
I can see that the two feet have the same age distribution.
It makes sense that most of the matches have home and away goals =< 2.
The max is significantly high, it's must be a powerful team.
Spain LIGA BBVA has the maximum goals with 8412 goals and Switzerland Super League has the minimum goals with 4166.
It is clear that each league team scores more goals on their lands.
All team attribute minimums are around the '20s and No maximum exceeds 80.
All teams that have defense scores above 53 went down over years.
The progress done from FC Sion was remarkable from 40 to 50.
FC Basel can be condidered as the best in improving because it kept its place
I'll explore these tables and select the important columns for me and start my analysis journey. Questions: 1- Is there any relationship between the height & the weight of the players? 2- Who is the best finisher and who is the fastest player? 3- Is there any relationship between the finishing score & the penalties of the players? 4- What is the preferred foot for the players? 5- What is the relation between the player's age and his overall rating? 6- What is the percentage of the attack & defense work rate? 7- What is the distribution of players' age, putting the preferred foot in consideration? 8- Which league has the maximum & minimum goals? 9- Which team has scored the maximum goals on his land during our timeframe? 10 - What teams improved their defense over the time period in the Switzerland Super League?
