umarhussain88

from sqlalchemy import create_engine
import pandas as pd 

params = urllib.parse.quote_plus(
        r'Driver={ODBC Driver 17 for SQL Server};'
        + fr'Server={sql_server}'
        + fr',1433;Database={sql_db};'
        + fr'Uid={sql_user};Pwd={sql_password};'
        + r'Encrypt=yes;TrustServerCertificate=Yes;Connection Timeout=30;')

umarhussain88

import numpy as np
NaN = np.nan 

def is_nums(numbers : tuple) -> bool:
    return all((isinstance(num, (int,float)) for num in numbers))
  
#is_nums(1, 4, 3, 2, 5)
#True
#is_nums(1, "a", 3)
#False

umarhussain88

import requests
import json
import base64
import pprint
import unittest
import time
import datetime

# Put this in contactMechList
ADDRESS_TEMPLATE = {

umarhussain88

CREATE PROCEDURE [stg_ecp].[p_InsertDwFactProductPrices]
	@jobKey	int
AS
BEGIN

	/* ==================================================================================================================
	Description:	Create Fact Table for Products.
	================================================================================================================== */

    SET NOCOUNT ON						-- Eliminate any dataset counts

umarhussain88

df = pd.read_csv('GlobalLandTemperaturesByCountry.csv')
df = df.dropna(subset=['AverageTemperature'])
df['dt'] = pd.to_datetime(df['dt'])
df = df[df['dt'].dt.year >= 1900]
df = df.drop(['AverageTemperatureUncertainty'], axis=1)
df_group = df.groupby(dfRead['dt'].dt.year)['AverageTemperature'].mean().reset_index() 

umarhussain88

{% extends '_base.html' %}
{% load crispy_forms_tags %}

    {% block javascript %}
    <!--Chart js-->
    <script src="https://cdnjs.cloudflare.com/ajax/libs/Chart.js/2.8.0/Chart.min.js" integrity="sha256-Uv9BNBucvCPipKQ2NS9wYpJmi8DTOEfTA/nH2aoJALw=" crossorigin="anonymous"></script>
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Chart.js/2.8.0/Chart.min.css" integrity="sha256-aa0xaJgmK/X74WM224KMQeNQC2xYKwlAt08oZqjeF0E=" crossorigin="anonymous" />
    <!-- jQuery -->
    <script src="https://code.jquery.com/jquery-3.3.1.min.js"></script>
    {% endblock javascript %}

umarhussain88

from django.db import models



class Carbon(models.Model):

    id = models.AutoField(
        primary_key=True,
        editable=False,
        

umarhussain88

from .models import Carbon 
from django.db.models import Q 
from django.views.generic import ListView
from datetime import datetime 



class CarbonDataView(ListView):
    model = Carbon 
    context_object_name = 'carbon'

umarhussain88

import pandas as pd

rows = [{'dt' : '2020-01-01 12:00:00'}, 
        {'dt' : '2020-01-04 13:00:00'}, 
        {'dt' : '2020-01-08 14:00:00'}, 
        {'dt' : '2020-01-09 15:00:00'}]

dt = pd.DataFrame(rows)
dt['dt'] = pd.to_datetime(dt['dt'],format='%Y-%m-%d')

umarhussain88

def generate_new_keys(*args,key='Carid',name='Carname'):
    """
    Takes in a number of dataframes and returns any duplicates with a new unique id. 
    groupby columns fixed to CarID and CarName.
    """
    # adds dictionaries into a single list.
    dicts_ = [arg.groupby(key)[name].first().to_dict() for arg in args]
    
    #merges dicts on unique key, this will exclude duplicates.
    merged_dicts = dict(ChainMap(*dicts_))