Syntax

All Syntax that I may need for future. (Probably won't. Just google it)

Libraries:

• Pandas: Helps load data frame to 2D array and perform actions on it
• Numpy: Very fast computational library for python
• Matplotlib/Seaborn: Used to draw visualization
• Sklearn: This model contains multiple libraries having pre-implemented functions to perform tasks from data preprocessing to model development and evaluation

Category Variables:

Steps:

• Import necessary libraries
• Load dataset
• Make list of all correct categorical value
• use the list to remove bogus values or correct it if enough data

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sb
from sklearn.preprocessing import LabelEncoder

# create a new dataframe with possible values for blood type
blood_type_categories = pd.DataFrame({
	'blood_type': ['A+', 'A-', 'B+', 'B-', 'AB+', 'AB-', 'O+', 'O-']
})
blood_type_categories