"""
# Hello World
"""
"""
Kaggle kernels are Jupyter Notebooks that are hosted in the cloud and have access to the all data as well as making submissions! They're worth trying out 👍

Below is a hyper-fast walk through of how to access the Music Classficiaton competition data
"""
"""
## Run Bash Commands
"""
!ls /kaggle/input/music-classification/kaggle
"""
## Import your fav Python libs
"""
import numpy as np
import pandas as pd
"""
## Read Music Classification Data
"""
"""
### Read Labels DataFrame
"""
ROOT_DIR = '/kaggle/input/music-classification/kaggle/'

## Read the training data labels csv file
dfLabels = pd.read_csv(ROOT_DIR + 'labels.csv')
dfLabels
"""
### Read Song DataFrame
"""
## Read individual song file
dfSong = pd.read_csv(ROOT_DIR + 'training/' + dfLabels.id[0], header=None)
dfSong
"""
## Visualizing your Song Data
"""
## Display wave form of song
# Aesthetics :
# - Select just the start of song, also apply some smoothing so its easier to see
# - Each column (ie song channel) is different color

dfSong[:200].rolling(5).mean().plot.line(figsize=(16,8), title="Song Wave Form (by Channel)")
## Plot distribution of values for each channel
# Aesthetics : 
# - Based on above graph, values typically fall between -100 and 100, trim bounds

dfSong.plot.density(xlim=(-100,100), figsize=(12, 8), title="Distribution of values for each channel")