Forums

import os
import re
import numpy as np
import pandas as pd
from flask import Flask, request

#Load data into Pandas dataframe
datafile = "movie_metadata_red.csv"
df = pd.read_csv(datafile, low_memory=False)

 from flask import Flask, render_template, request #os
 import pandas as pd

 app = Flask(__name__)
 import pandas as pd

 @app.route('/', methods=['GET', 'POST'])
 def index():
 return render_template('index.html')


@app.route('/data', methods=['GET', 'POST'])

def data():
if request.method == 'POST':
    file = request.form['upload-file']

    url = "/home/vojtaripa/mysite/" + file  
    col_list = ['txt', 'resp', 'txt_proc', 'link']
    df_quest = pd.read_csv(url, usecols=col_list, encoding='utf-8')
    return render_template('data.html', data=df_quest.to_html())

FileNotFoundError: [Errno 2] No such file or directory: '/home/vojtaripa/mysite/testCSV.csv'

    def create_well_recommendation_map(
        user_latitude, user_longitude, threshold_distance=float(thresh)
    ):

        file_path = "/home/varad2004/mysite/dugwell.csv"
        df = pd.read_csv(file_path)

        df = df.dropna(subset=["Y", "X", "Depth (m.bgl)", "Well Type"])

        X = df[["Y", "X"]]
        y_depth = df["Depth (m.bgl)"]
        y_well_type = df["Well Type"]

        depth_model = KNeighborsRegressor(n_neighbors=3)
        depth_model.fit(X, y_depth)

        well_type_model = KNeighborsClassifier(n_neighbors=3)
        well_type_model.fit(X, y_well_type)

        def recommend_well_and_nearest(user_lat, user_lon):
            user_location = [[user_lat, user_lon]]

            nearest_dugwell_index = depth_model.kneighbors(user_location)[1][0][0]
            nearest_dugwell_coordinates = X.iloc[nearest_dugwell_index]
            nearest_dugwell_depth = y_depth.iloc[nearest_dugwell_index]
            nearest_dugwell_well_type = y_well_type.iloc[nearest_dugwell_index]

            distance_to_nearest_dugwell = geodesic(
                user_location[0], nearest_dugwell_coordinates
            ).kilometers
            if distance_to_nearest_dugwell > threshold_distance:
                return f"No suitable well within {threshold_distance} km.", None, None

            return (
                nearest_dugwell_depth,
                nearest_dugwell_well_type,
                nearest_dugwell_coordinates,
            )

        map_center = [user_latitude, user_longitude]
        map_object = folium.Map(location=map_center, zoom_start=12)

        recommendation_result = recommend_well_and_nearest(
            user_latitude, user_longitude
        )
        recommended_depth, recommended_well_type, recommended_coordinates = (
            recommendation_result
        )

        if (
            isinstance(recommended_well_type, str)
            and recommended_well_type != "No suitable well within 3 km."
        ):

            folium.Marker(
                location=[user_latitude, user_longitude],
                popup=f"Recommended Depth: {recommended_depth} meters, Recommended Well Type: {recommended_well_type}",
                icon=folium.Icon(color="red"),
            ).add_to(map_object)

            folium.Marker(
                location=[recommended_coordinates["Y"], recommended_coordinates["X"]],
                popup=f"Nearest Well - Depth: {recommended_depth} meters, Well Type: {recommended_well_type}",
                icon=folium.Icon(color="green"),
            ).add_to(map_object)
        else:

            folium.Marker(
                location=[user_latitude, user_longitude],
                popup="No suitable well within 3 km.",
                icon=folium.Icon(color="gray"),
            ).add_to(map_object)

        return map_object, recommended_depth, recommended_well_type

    user_latitude = user_lat
    user_longitude = user_lon

    map_object, recommended_depth, recommended_well_type = (
        create_well_recommendation_map(user_latitude, user_longitude)
    )

    print(f"Recommended Depth: {recommended_depth} meters")
    print(f"Recommended Well Type: {recommended_well_type}")

    map_object.save("well_recommendation_map.html")

    with open("well_recommendation_map.html", "r") as file:

        html_content = file.read()

    result = {
        "depth": f"{recommended_depth}",
        "well_type": f"{recommended_well_type}",
        "html_content": f"{html_content}",
    }

    return result