<jupyter_start><jupyter_text><jupyter_code>import os
import pandas as pd
import numpy as np
import json
import random, string
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
import requests
import requests, zipfile

#the url and auth_value from the website 
url = 'https://api.zindi.africa/v1/competitions/bloodsai-blood-spectroscopy-classification-challenge/files/OrginalData.zip'
myobj = {'auth_token': '<PASSWORD>'} #use your own

x = requests.post(url, data = myobj,stream=True)
target_path = 'OriginalData.zip'

handle = open(target_path, "wb")
for chunk in x.iter_content(chunk_size=512):
    if chunk:  # filter out keep-alive new chunks
        handle.write(chunk)
handle.close()

!unzip -qq /content/OriginalData.zip
#maindir = "data/OriginalData" # Directory with your files
traincsv = "/content/Train.csv"
testcsv = "/content/Test.csv"
train = pd.read_csv(traincsv)
train.head()
ldl = train
ldl = ldl.drop(['hemoglobin(hgb)_human','hdl_cholesterol_human'],axis=1)
ldl.sort_values(by=['cholesterol_ldl_human'])
ldl.iloc[13139].iloc[1:171].plot()
ldl.iloc[9389].iloc[1:171].plot()
ldl.iloc[3666].iloc[1:171].plot()
ldl.iloc[9384].iloc[1:171].plot()
ldl.iloc[9383].iloc[1:171].plot()
ldl_filtered = ldl[ldl['cholesterol_ldl_human'] == 'ok']
ldl_filtered.head(15)
ldl_filtered.iloc[0].iloc[1:171].plot()
ldl_filtered.iloc[1].iloc[1:171].plot()
ldl_filtered.iloc[2].iloc[1:171].plot()
ldl_filtered.iloc[4].iloc[1:171].plot()
ldl_filtered.iloc[6].iloc[1:171].plot()
ldl_filtered.iloc[7].iloc[1:171].plot()
ldl_filtered.iloc[9].iloc[1:171].plot()
ldl_filteredlow =ldl[ldl['cholesterol_ldl_human'] == 'low']
ldl_filteredlow.head(15)
ldl_filteredlow.iloc[3].iloc[1:171].plot()
ldl_filteredlow.iloc[5].iloc[1:171].plot()<jupyter_output><empty_output>
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