rohitrajiit

import gradio as gr
from openai import OpenAI
import docx2txt
import PyPDF2


api_key = "sk-"  # Replace with your key

def read_text_from_file(file_path):
    # Check the file type and read accordingly

rohitrajiit

import requests
from bs4 import BeautifulSoup
import pandas as pd

def matchbymatch(id):
    urlformat = 'https://stats.espncricinfo.com/ci/engine/player/{}.html?class=2;template=results;type=allround;view=match'.format(id)
    page = requests.get(urlformat)
    bs = BeautifulSoup(page.content, 'lxml')
    rows = bs.find_all('tr',class_='data1')
    data = []

rohitrajiit

import os
from io import BytesIO
import tarfile
import tempfile
from six.moves import urllib

from matplotlib import gridspec
from matplotlib import pyplot as plt
import numpy as np
from PIL import Image

rohitrajiit

import tensorflow as tf
import tensorflow_hub as hub
import matplotlib.pyplot as plt
import numpy as np
import PIL.Image

def load_img(path_to_img):
  max_dim = 512
  img = tf.io.read_file(path_to_img)
  img = tf.image.decode_image(img, channels=3)

rohitrajiit

import requests
import pandas
import json
import plotly.express as px

districts_daily = requests.get('https://api.covid19india.org/v4/timeseries.json')
districts_daily = districts_daily.text
districts_daily = json.loads(districts_daily)

dfs = []

rohitrajiit

active = []
confirmed = []
deaths = []
deltaconfirmed = []
deltadeaths = []
deltarecovered = []
recovered = []
state = []
for data in districts_daily['statewise']:
    active.append(data['active'])

rohitrajiit

import plotly.graph_objects as go
import requests
import pandas
import json


districts_daily = requests.get('https://api.covid19india.org/data.json')

districts_daily = districts_daily.text
districts_daily = json.loads(districts_daily)

rohitrajiit

import plotly.express as px

fig = px.line(df, x="date", y=["totalactive",'totalrecovered','totaldeceased'], 
              log_y= True, title='Total Coronavirus Cases in India')
fig.show()

rohitrajiit

with open('Indian_States.txt') as f:
    statejson = json.load(f)
fig = px.choropleth_mapbox(statedf, geojson=statejson, color="active",
                           locations="state", featureidkey="properties.NAME_1",
                           center={"lat": 23.2599, "lon": 77.4126},
                           mapbox_style="carto-positron", zoom=3)
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()

rohitrajiit

px.scatter(data2, x="totalconfirmed", y="totaldeceased", 
           animation_frame=data2.date.astype(str), animation_group="state",
           size="totaltested", color="state", hover_name="state", 
           range_x=[0,450000], range_y=[0,16000]
           )