Pinned Repositories
LGM-NewReact-app.github.io
shape_Ai_project_Vishakha_goyal
import requests import os from datetime import datetime userAPI = "0f2585f6544ef75a6f06304e1ecc1b8d" location = input("Enter The City Name :- ") completeAPIlink = "https://api.openweathermap.org/data/2.5/weather?q={}&appid={}" api_link = requests.get(completeAPIlink) api_data = api_link.json() if api_data["cod"] == "404": print("Invalid City :- {}, Please check your city name".format(location)) else: temp_city = ((api_data ["main "]['temp'])-273.15) wethr_des = api_data['weather'][0][' description '] humdt = api_data["main"]['humidity'] wind_spd = api_data['wind']['speed'] date_time = datetime.now().strftime("%d %b %Y | %I:%M %S %p") print("-------------------------------------------------------------------") print("Weather Starts for - {} || {}".format(location.upper(), date_time)) print("-------------------------------------------------------------------") print("Current Temperature is : { :.2f} deg C".format(temp_city)) print("Current Weather Description :- ", wether_des) print("Current Humidity :- ", humdt , '%') print("Current Wind Speed :- ", wind_spd, 'kmph') f = open("api_data", 'w')
-Vishakha-Goyal---Network-security
Python and network security bootcamp project repo , Vishakha Goyal
IPLDASHBOARDPROJECT
jupyter-kernel
Wrapper Kernel for MetaCall Core Library leveraging IPython and Jupyter
PRODIGY_DS_TASK1
PRODIGY_DS_TASK2
PRODIGY_DS_TASK4
Analyzing and visualizing sentiment patterns in social media data offers a powerful means to grasp public opinion and attitudes concerning particular topics or brands. By employing sentiment analysis techniques on textual content from social media platforms, such as Twitter, Facebook ... etc
Python_therapy.github.io
vishakha-goyal
Config files for my GitHub profile.
vishakha-goyal's Repositories
vishakha-goyal/IPLDASHBOARDPROJECT
vishakha-goyal/PRODIGY_DS_TASK2
vishakha-goyal/PRODIGY_DS_TASK4
Analyzing and visualizing sentiment patterns in social media data offers a powerful means to grasp public opinion and attitudes concerning particular topics or brands. By employing sentiment analysis techniques on textual content from social media platforms, such as Twitter, Facebook ... etc
vishakha-goyal/PRODIGY_DS_TASK1
vishakha-goyal/jupyter-kernel
Wrapper Kernel for MetaCall Core Library leveraging IPython and Jupyter
vishakha-goyal/LGM-NewReact-app.github.io
vishakha-goyal/Python_therapy.github.io
vishakha-goyal/-Vishakha-Goyal---Network-security
Python and network security bootcamp project repo , Vishakha Goyal
vishakha-goyal/shape_Ai_project_Vishakha_goyal
import requests import os from datetime import datetime userAPI = "0f2585f6544ef75a6f06304e1ecc1b8d" location = input("Enter The City Name :- ") completeAPIlink = "https://api.openweathermap.org/data/2.5/weather?q={}&appid={}" api_link = requests.get(completeAPIlink) api_data = api_link.json() if api_data["cod"] == "404": print("Invalid City :- {}, Please check your city name".format(location)) else: temp_city = ((api_data ["main "]['temp'])-273.15) wethr_des = api_data['weather'][0][' description '] humdt = api_data["main"]['humidity'] wind_spd = api_data['wind']['speed'] date_time = datetime.now().strftime("%d %b %Y | %I:%M %S %p") print("-------------------------------------------------------------------") print("Weather Starts for - {} || {}".format(location.upper(), date_time)) print("-------------------------------------------------------------------") print("Current Temperature is : { :.2f} deg C".format(temp_city)) print("Current Weather Description :- ", wether_des) print("Current Humidity :- ", humdt , '%') print("Current Wind Speed :- ", wind_spd, 'kmph') f = open("api_data", 'w')
vishakha-goyal/vishakha-goyal
Config files for my GitHub profile.