Introducing my own personal sprint training “50 Days of Kaggle”

The task is simple:

Improve Kaggle score by the end of 50 days
Work on ML models daily. Try interacting on the portal as much as possible.
Keep ISLR notes handy. Blog over here for revision
Use Python. Or else use R Tidymodels. (neither of which I am currently proficient in)

I’d want to use this blog to journal my progress. Hopefully by 26th Nov’22, I’d have improved from where I’m starting out.

So what do we have for Day 1?

The Titanic Dataset

Everyone’s first starting point. And I’m slowly starting to appreciate why. Lets see if we can read the data directly into this notebook

Reading the data

First things first, import libraries

Code

import requests
import numpy as np
import pandas as pd
import kaggle

kaggle.api.authenticate()

Note to self: below command did not work

Code

#kaggle.api.dataset_download_files("titanic", path = ".", unzip = True)

However, this one does as per this link https://www.kaggle.com/general/138914

Code

kaggle.api.competition_download_files("titanic", path = ".")

This pulls the .zip file in the local folder. because this is a zip file, we need package called zipfile(note to self: don’t forget the console command reticulate::py_install("zipfile"))

https://stackoverflow.com/a/56786517/7938068

Reading and checking the first rows of train

Code

import zipfile

zf = zipfile.ZipFile("titanic.zip")
train = pd.read_csv(zf.open("train.csv"))
test = pd.read_csv(zf.open("test.csv"))
train.head()

	PassengerId	Survived	Pclass	Name	Sex	Age	SibSp	Ticket	Fare	Cabin	Embarked
0	1	0	3	Braund, Mr. Owen Harris	male	22.0	1	A/5 21171	7.2500	NaN	S
1	2	1	1	Cumings, Mrs. John Bradley (Florence Briggs Th...	female	38.0	1	PC 17599	71.2833	C85	C
2	3	1	3	Heikkinen, Miss. Laina	female	26.0	0	STON/O2. 3101282	7.9250	NaN	S
3	4	1	1	Futrelle, Mrs. Jacques Heath (Lily May Peel)	female	35.0	1	113803	53.1000	C123	S
4	5	0	3	Allen, Mr. William Henry	male	35.0	0	373450	8.0500	NaN	S

Checking the first rows of test

Code

test.head()

	PassengerId	Pclass	Name	Sex	Age	SibSp	Parch	Ticket	Fare	Cabin	Embarked
0	892	3	Kelly, Mr. James	male	34.5	0	0	330911	7.8292	NaN	Q
1	893	3	Wilkes, Mrs. James (Ellen Needs)	female	47.0	1	0	363272	7.0000	NaN	S
2	894	2	Myles, Mr. Thomas Francis	male	62.0	0	0	240276	9.6875	NaN	Q
3	895	3	Wirz, Mr. Albert	male	27.0	0	0	315154	8.6625	NaN	S
4	896	3	Hirvonen, Mrs. Alexander (Helga E Lindqvist)	female	22.0	1	1	3101298	12.2875	NaN	S

This took me a whole day to figure out. End of Day1 🤷‍♂️