Thank you for the replies. Is there a way to go back to a completed challenge to play with it more? Or are you stuck once the solution is showing
There are no playoffs in La Liga. Those years with more matches were unique because there were 22 teams playing instead of the regular 20.
For a while I thought “1 season” meant the first season and was very confused. Turns out 1. and 4. asks for the max and min out of all seasons.
I will be moderating this forum till 10 AM EST.
Feel free to keep the conversation around the challenge alive.
Fun challenge! I enjoy the direction we are taking with moving onto pandas.
How To See The Entire Data Set
Use Print() Method
Carousel21 mentioned that you can see the entire dataset by using the
print() method. E.g. by doing something like:
Use Head() Method
Another way is to pass in the total number of rows (or a larger number than the total) into the head function. E.g. by writing one of the below
instead of just
to get all 33 rows. The reason that
df.head() gives only the first 5 rows (row “0” to row “4”) is because 5 is the default number of rows for the
Head() Function Documentation
Here’s the documentation that explains how the head() function works:
This is absolutely correct!
When you don’t know sports and English isn’t your primary language all the abreviations of the table mean nothing.
MP W D L GF GA GD
Is D for Defeat and L for Losses, doesn’t make sense, if it’s both the same.
I think it could be D for Draw
Hi all, I will be moderating the forum for the next 2 hours. Please let me know if you face any barriers in attempting to complete todays challenge. Also, please remember to not share any answers on this forum.
MP - Matches Played
W - Won
D - Draw
L - Lost
GF - Goals For
GA - Goals Against
GD - Goal Difference (GF - GA)
I’ve been using replit to run Python and
import pandas as pd is returning an error.
ModuleNotFoundError: No module named 'pandas'. Is there anything I can do there or does this challenge have to be done on Jupyter?
I would recommend using the Jupiter notebook provided
Although not part of the challenge, how can we do the min, max, etc for a certain group of data from the entire dataset? For example, if I wanted to only look at the maximum wins for a country “es CAD” in the data set, how could I write that out as
wins.max() would just look at the entire set?
Interesting question. I want to look further into this too. (sorry, I can’t help, this is the first time I’ve ever seen Pandas and need a bit to get it.)
in the links for this challenge ( Using Pandas and Python to Explore Your Dataset – Real Python )there is some stuff under ‘Exploratory Data Analysis’ that might be helpful.
hoping there is more coming in the next few days that will give us a chance to try this out.
Fun challenge! Didn’t get confusing and applies practice of common functions for reiteration.
GF? GA? GD? I see that I don’t know anything about soccer.
Thanks, @Denverdias for this!
Someone posted an explanation of how to do this (or something very close to this), here:
Aww, thanks for finding an answer.