Machine Learning with Python | Geocoding and Reverse Geocoding using Python- P76

Publié le: 13 juin 2018
sur la chaîne: technologyCult

3,198

Machine Learning with Python | Geocoding and Reverse Geocoding using Python- P76

Session # 76

Topic to be covered - Geocode and Reverse Geocode

Geocoding is the process of transforming a description of a location—such as a pair of coordinates, an address, or a name of a place—to a location on the earth's surface. You can geocode by entering one location description at a time or by providing many of them at once in a table. The resulting locations are output as geographic features with attributes, which can be used for mapping or spatial analysis.

You can quickly find various kinds of locations through geocoding. The types of locations that you can search for include points of interest or names from a gazetteer, like mountains, bridges, and stores; coordinates based on latitude and longitude or other reference systems, such as the Military Grid Reference System (MGRS) or the U.S. National Grid system; and addresses, which can come in a variety of styles and formats, including street intersections, house numbers with street names, and postal codes.

Code Starts Here
==============

from geopy.geocoders import Nominatim

geolocator = Nominatim()

city = 'kolkata'
country = 'India'

Both City and Country
loc = geolocator.geocode(str(city + ','+ country))

print(loc.latitude,loc.longitude)

loc1 = geolocator.geocode(country)
print(loc1.latitude, loc1.longitude)

from pygeocoder import Geocoder

result = Geocoder.reverse_geocode(19.1334321,72.8882172)

print(result.coordinates)
print(result.country)
print(result.city)
print(result.administrative_area_level_1)
print(result.administrative_area_level_2)

address1 = Geocoder.geocode('221B Baker Street,LONDON NW1 6XE')

print(address1.street_number)

print(address1.route)

print(address1.city)
print(address1.country)
print(address1.administrative_area_level_1)
print(address1.administrative_area_level_2)

All Playlist of this youtube channel
====================================

1. Data Preprocessing in Machine Learning
   • Data Preprocessing in Machine Learning| Li...

2. Confusion Matrix in Machine Learning, ML, AI
   • Confusion Matrix in Machine Learning, ML, AI

3. Anaconda, Python Installation, Spyder, Jupyter Notebook, PyCharm, Graphviz
   • Anaconda | Python Installation | Spyder | ...

4. Cross Validation, Sampling, train test split in Machine Learning
   • Cross Validation | Sampling | train test s...

5. Drop and Delete Operations in Python Pandas
   • Drop and Delete Operations in Python Pandas

6. Matrices and Vectors with python
   • Matrices and Vectors with python

7. Detect Outliers in Machine Learning
   • Detect Outliers in Machine Learning

8. TimeSeries preprocessing in Machine Learning
   • TimeSeries preprocessing in Machine Learning

9. Handling Missing Values in Machine Learning
   • Handling Missing Values in Machine Learning

10. Dummy Encoding Encoding in Machine Learning
   • Label Encoding, One hot Encoding, Dummy En...

11. Data Visualisation with Python, Seaborn, Matplotlib
   • Data Visualisation with Python, Matplotlib...

12. Feature Scaling in Machine Learning
   • Feature Scaling in Machine Learning

13. Python 3 basics for Beginner
   • Python | Python 3 Basics | Python for Begi...

14. Statistics with Python
   • Statistics with Python

15. Sklearn Scikit Learn Machine Learning
   • Sklearn Scikit Learn Machine Learning

16. Python Pandas Dataframe Operations
   • Python Pandas Dataframe Operations

17. Linear Regression, Supervised Machine Learning
   • Linear Regression | Supervised Machine Lea...

18 Interview Questions on Machine Learning, Artificial Intelligence, Python Pandas and Python Basics
   • Interview Question for Machine Learning, D...

19. Jupyter Notebook Operations
   • Jupyter and Spyder Notebook Operations in ...

Sur cette page du site, vous pouvez voir la vidéo en ligne Machine Learning with Python | Geocoding and Reverse Geocoding using Python- P76 durée heure minute seconde en bonne qualité , qui a été Téléchargé par l'utilisateur technologyCult 13 juin 2018, Partagez le lien avec vos amis et connaissances, sur youtube cette vidéo a déjà été regardée 3,198 fois et il a aimé 26 téléspectateurs. Bon visionnage!

158