Vaccine Update Dashboard

# System from datetime import datetime import requests import os # DataFrame import pandas as pd # Visualization import plotly.express as px import plotly.graph_objects as go import pycountry # SQL Database from sqllex import * from sqllex.types import SQLRequest

vaccine_db = SQLite3x(path="Database/vaccine_data.db")

df = pd.read_html( "https://www.pharmaceutical-technology.com/covid-19-vaccination-tracker/" ) data = pd.DataFrame(df[0]) data["Fully Vaccinated Population (%)"] = ( data["Fully Vaccinated Population (%)"].str.replace("%", "").astype("float") )/100 data["Fully Vaccinated Population (%)"] = data["Fully Vaccinated Population (%)"].astype("str")\ + " %" data.head()

UPDATE = True World_dose_df = data["Doses Administered"].values[0] World_dose_sql = vaccine_db.select(SELECT="Doses_Administered", FROM="World")[-1][0] if World_dose_df == World_dose_sql: UPDATE = False print("No New Updates") else: UPDATE = True print("Update the entire database")

# datetime object containing current date and time now = datetime.now() dt_string = now.strftime("%d/%m/%Y %H:%M:%S") data["Date_Time"] = dt_string

vaccine_db.updatemany("Total", data.drop(columns="Date_Time", axis=1).values)

if UPDATE: vaccine_db.insertmany( "Pakistan", data[data["Country"] == "Pakistan"].drop(columns="Country", axis=1).values, ); vaccine_db.insertmany( "World", data[data["Country"] == "World"].drop(columns=["Country","Vaccine being used in a country"], axis=1).values );

vaccine_db.execute( "SELECT Country,Fully_Vaccinated_Population FROM Total WHERE Doses_per_1000 > 200 LIMIT 5" )

vaccine_db.select("Pakistan", ALL, LIMIT= 2)

vaccine_db.select("World", ALL, LIMIT= 2)

for column_name in vaccine_db.get_columns_names('World'): print(column_name)

pakistan = pd.DataFrame( vaccine_db.select("Pakistan"), columns=[ "Doses Administered", "Doses per 1000", "Fully Vaccinated Population (%)", "Vaccine being used in a country", "Date_Time", ], ) pakistan["Date_Time"] = pd.to_datetime( pakistan["Date_Time"], format="%d/%m/%Y %H:%M:%S", errors="ignore" ) pakistan.sort_values(by="Date_Time", inplace=True) world = pd.DataFrame( vaccine_db.select("World"), columns=[ "Doses Administered", "Doses per 1000", "Fully Vaccinated Population (%)", "Date_Time", ], ) world["Date_Time"] = pd.to_datetime( world["Date_Time"], format="%d/%m/%Y %H:%M:%S", errors="ignore" ) total = pd.DataFrame( vaccine_db.select("Total"), columns=[ "Country", "Doses Administered", "Doses per 1000", "Fully Vaccinated Population (%)", "Vaccine being used in a country", ], )

world["Fully Vaccinated Population (%)"] = ( world["Fully Vaccinated Population (%)"].str.replace("%", "").astype("float") ) total["Fully Vaccinated Population (%)"] = ( total["Fully Vaccinated Population (%)"].str.replace("%", "").astype("float") ) pakistan["Fully Vaccinated Population (%)"] = ( pakistan["Fully Vaccinated Population (%)"].str.replace("%", "").astype("float") )

pakistan.tail(2)

world.tail(2)

world.to_csv("Kaggle/World-Vaccine-Progress/world_time_series.csv",index=False) total.to_csv("Kaggle/World-Vaccine-Progress/World_Vaccination_Progress.csv",index=False) pakistan.to_csv("Kaggle/World-Vaccine-Progress/pakistan_time_series.csv",index=False)

message = str("New Update : " + dt_string)

!echo $message

if UPDATE: !kaggle datasets version -p /work/Kaggle/World-Vaccine-Progress -m "$message"

pakistan["Country"] = "Pakistan" world["Country"] = "World" world_pak = pd.concat([pakistan, world]) fig = px.line( world_pak, x="Date_Time", y="Doses Administered", log_y=True, color="Country", title="Dose Administered", ) fig.show()

fig = px.line( world_pak, x="Date_Time", y="Doses per 1000", color="Country", title="Doses per 1000", ) fig.show()

fig = px.line( world_pak, x="Date_Time", y="Fully Vaccinated Population (%)", color="Country", title="Fully Vaccinated Population (%)", ) fig.show()

fig = px.bar( world_pak.sort_values(by="Date_Time").tail(2), x="Country", y="Fully Vaccinated Population (%)", ) fig.show()

total.drop(0, axis=0, inplace=True) fig = px.scatter( total.head(10), x="Doses per 1000", y="Doses Administered", size="Fully Vaccinated Population (%)", color="Country", title="World Vaccine Data", hover_name="Country", log_x=True, size_max=60, ) fig.show()

fig = px.pie( total.head(10), values="Fully Vaccinated Population (%)", names="Country", title="World Fully Vaccinated Population (%)", ) fig.show()

geo = pd.read_csv("Database/countries.csv") geo_total = pd.merge( total, geo, how="left", on="Country" ) geo_total.head(2)

fig = px.scatter_mapbox( geo_total, lat="Latitude", lon="Longitude", color="Fully Vaccinated Population (%)", size="Doses Administered", color_continuous_scale="Inferno", size_max=50, hover_data=["Country"], mapbox_style="carto-positron", zoom=0.5, ) fig.update_layout(margin={"r": 0, "t": 0, "l": 0, "b": 0}) fig.show()

fig = px.bar( total, x="Country", y="Fully Vaccinated Population (%)", log_y=True, title="World Fully Vaccinated Population", ).update_xaxes(categoryorder="total ascending") fig.show()

fig = px.bar( total, x="Country", y="Doses Administered", log_y=True, title="World Fully Doses Administered", ).update_xaxes(categoryorder="total descending") fig.show()

def telegram_sendtext(bot_message): send_text = ( "https://api.telegram.org/bot" + os.environ["TELE_TOKEN"] + "/sendMessage" ) response = requests.get( send_text, params={ "chat_id": os.environ["TELE_BOT_ID"], "parse_mode": "Markdown", "text": bot_message, }, ) return response.json()

def update_msg(): tail = world.tail(1).values names = ["Doses Administered", "Doses per 1000", "Fully Vaccinated Population (%)"] col = [0, 1, 2] telegram_sendtext("New Update at " + str(tail[0, 4])); T_text = [] for n, c in zip(names, col): Text = n + " : " + str(tail[0, c]) T_text.append(Text) telegram_sendtext(str(T_text));

if UPDATE: update_msg() else: telegram_sendtext("No Update Today")