#!/usr/bin/env python3
# -*- coding: utf-8 -*-

"""
Felix Muzny
12/2/2022
DS 2000
Lecture 23 - timing experiments

Logistics:
        
    - OH for the rest of the semester 
        - 4 - 8pm
        - we're happy to help you with DS 2001
        projects AND expect to explain your project/goal
        to the TA a bit to get help to start with :)
        
    - remote attendance (https://bit.ly/remote-ds2000-muzny)
    
    - Now playing:
        santé (stromae)
        
Warm-up 0:
    Do you listen to music on spotify?
    A. yes
    B. nope!
    
Dec 1st:
    wrapped came out
    summary of your yearly music listening statistics
    

Three ways to participate in multiple choice questions
 1) via the PollEverywhere website: https://pollev.com/muzny
 2) via text: text "muzny" to the number 22333 to join the session
 3) via Poll Everywhere app (available for iOS or Android)
"""


"""
Spotify Wrapped Day
---

(slides)


1. how many genres you listened to
2. which were your top genres
3. what kinds of music you listened to at different times of day
4. total play time
5. what song you listened to the most
6. how many songs you listened to and your top five songs
7. your top 100 songs
8. how many artists you listened to
9. what your top artist was (by minutes)
10. what percentile of people listening to that artist you are in
11. your top 5 artists
12. your listening personality

What data do we need to answer these questions?

https://www.spotify.com/us/account/privacy/
    - you can request all your streaming data
    - it take 5 days to get it, but spotify will gather it for you

"""


"""
All your questions!
----

Next Tuesday, we'll be doing a combo lecture of some trivia and
an opportunity for you all to ask me anything that you're curious about.

Spend a minute filling out the survey here to submit questions:
    
    https://bit.ly/ds2000finalday

"""

# Now playing (the song that Felix listened to 40 times last year)
# slå mig hårt i ansiktet (thomas stenström)




"""
DataFrame warm-ups/review
----

Say that I've loaded a data frame in as follows:

"""
import pandas as pd

df = pd.read_csv("movies.csv")
print(df)
df.info()
print()

"""
what code can you use to find how many rows 
are in the data frame?
"""
# (rows, columns) -> tuple (an immutable list)
print(df.shape)
print(df.shape[0])
print(len(df))
print()

"""
what code can you use to find how many columns 
are in the data frame?
"""
print(df.shape[1])
print()

"""
what code can you use to find the maximum value 
in the IMDB column?
"""
# first fetching the IMDB column, then calc the max
print(df["IMDB"].max())
print()

"""
what code can you use to find the row 
number of the maximum value in the 
IMDB column?
"""
# when you want the thing (normally an index)
# associated with the row with the max value
# this is called an argmax (or argmin)
print(df["IMDB"].argmax())
print()


"""
what code can you use to find a 
single specific row?
"""
# a single set of square brackets is giving
# me a Series (pandas 1d data object)
# 2 square brackets gets me a DataFrame
# (2d data object)
print(df.iloc[[0]])
print(df.iloc[[df["IMDB"].argmax()]])
print(df.iloc[[df["IMDB"].argmin()]])




# Next Time
# ---
#     - Ask Felix Anything
#     - Trivia/Review