Answers for "space weather dashboard build your own custom dashboard to analyze and predict weather"

space weather dashboard build your own custom dashboard to analyze and predict weather

import sqlite3
conn = sqlite3.connect("space.db", isolation_level=None)
cur = conn.cursor()cur.execute('''
    CREATE TABLE sunspots (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    date DATE,
    sunspot_count INTEGER,
    sunspot_sd REAL,
    sunspot_obs_no INTEGER
    );
    ''')

space weather dashboard build your own custom dashboard to analyze and predict weather

import json
import urlliburl_mag="https://services.swpc.noaa.gov/products/solar-wind/mag-7-day.json"
url_plasma="https://services.swpc.noaa.gov/products/solar-wind/plasma-7-day.json"mag=urllib.request.urlopen(url_mag)
plasma=urllib.request.urlopen(url_plasma)mag_json=json.loads(mag.read())
plasma_json=json.loads(plasma.read())

space weather dashboard build your own custom dashboard to analyze and predict weather

import pandas as pd
import numpy as npdf = pd.DataFrame(columns = ["Date", "Sunspot_count", "Sunspot_sd", "Observ_No"])

space weather dashboard build your own custom dashboard to analyze and predict weather

import ftplib#Open ftp connection
ftp = ftplib.FTP('ftp.seismo.nrcan.gc.ca', 'anonymous',
'user')#List the files in the current directory
print("File List:")
files = ftp.dir()import datetimenow=datetime.datetime.now()
ftp.cwd("intermagnet/minute/provisional/IAGA2002/" + str(now.year) + "/" + str(now.strftime("%m")))
# files = ftp.dir()

space weather dashboard build your own custom dashboard to analyze and predict weather

for line in fileobject:
    row_bytes = line.split()

    date = row_bytes[0].decode("utf-8") + "-" + row_bytes[1].decode("utf-8") + "-" + row_bytes[2].decode("utf-8")    row_txt = [date, row_bytes[4].decode("utf-8"), row_bytes[5].decode("utf-8"), row_bytes[6].decode("utf-8")]    a_series = pd.Series(row_txt, index = df.columns)
    
    query = 'INSERT INTO sunspots (date, sunspot_count, sunspot_sd, sunspot_obs_no) VALUES ("%s", "%s", "%s", "%s")' % (a_series["Date"], a_series["Sunspot_count"], a_series["Sunspot_sd"], a_series["Observ_No"])    cur.execute(query)

space weather dashboard build your own custom dashboard to analyze and predict weather

for file in file_list:
    station = ''
    lat = 0
    long = 0
    
    date_today = str(now.year) + str(now.strftime("%m")) + str(now.strftime("%d"))
    
    if(date_today in file):
        ftp.retrbinary("RETR " + file, open(file, 'wb').write)
        temp=open(file, 'rb')
        
        data_rows = 0        for line in temp:    
            if(data_rows == 1):
                row_bytes = line.split()
                date_time = row_bytes[0].decode("utf-8") + " " + row_bytes[1].decode("utf-8")[:8]
                row_txt = [date_time, row_bytes[3].decode("utf-8"), row_bytes[4].decode("utf-8"), row_bytes[5].decode("utf-8"), row_bytes[6].decode("utf-8")]
                
                a_series = pd.Series(row_txt, index = df.columns)
    
                query = 'INSERT INTO geo_mag (station, lat, long, date_time, bx, by, bz, bf) VALUES ("%s", "%s", "%s", "%s", "%s", "%s", "%s", "%s")' % (station, lat, long, a_series["Date_time"], a_series["Bx"], a_series["By"], a_series["Bz"], a_series["Bf"])                cur.execute(query)else:
                if('IAGA Code' in line.decode("utf-8") or 'IAGA CODE' in line.decode("utf-8")):
                    station = line.decode('utf-8').split()[2]
                    print(station)
                elif('Latitude' in line.decode("utf-8")):
                    lat = line.decode('utf-8').split()[2]
                elif('Longitude' in line.decode("utf-8")):
                    long = line.decode('utf-8').split()[2]
                elif('DATE       TIME' in line.decode("utf-8")):
                    data_rows = 1        conn.commit()