Learn practical skills, build real-world projects, and advance your career

Sarawak Populated Areas 2020

The populated areas in Sarawak affects the development of the landuse in the region. Being a multi-ethnic state in Malaysia, it is also the biggest and has the biggest natural resources compared to its sister states. Higher demands of infrastructural development and economic demands are dependent on the population of the different regions in Sarawak. For that purposes, we'll be observing the population of the different populated areas in Sarawak to understand the possibility of developmental demands of the region.

NOTE:
This notebook is a work in progress and will continuously be revised and reviewed to produce an adequate baseline for Exploratory Spatial Data Analysis (ESDA). Further elaborations or discussions of any updates will be shared at the following platforms:

!pip install jovian opendatasets --upgrade --quiet
!pip install geopandas
Requirement already satisfied: geopandas in /srv/conda/envs/notebook/lib/python3.8/site-packages (0.8.1) Requirement already satisfied: shapely in /srv/conda/envs/notebook/lib/python3.8/site-packages (from geopandas) (1.7.1) Requirement already satisfied: pandas>=0.23.0 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from geopandas) (1.1.2) Requirement already satisfied: pyproj>=2.2.0 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from geopandas) (2.6.1.post1) Requirement already satisfied: fiona in /srv/conda/envs/notebook/lib/python3.8/site-packages (from geopandas) (1.8.17) Requirement already satisfied: numpy>=1.15.4 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from pandas>=0.23.0->geopandas) (1.19.1) Requirement already satisfied: python-dateutil>=2.7.3 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from pandas>=0.23.0->geopandas) (2.8.1) Requirement already satisfied: pytz>=2017.2 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from pandas>=0.23.0->geopandas) (2020.1) Requirement already satisfied: six>=1.7 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from fiona->geopandas) (1.15.0) Requirement already satisfied: cligj>=0.5 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from fiona->geopandas) (0.5.0) Requirement already satisfied: click<8,>=4.0 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from fiona->geopandas) (7.1.2) Requirement already satisfied: attrs>=17 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from fiona->geopandas) (19.3.0) Requirement already satisfied: munch in /srv/conda/envs/notebook/lib/python3.8/site-packages (from fiona->geopandas) (2.5.0) Requirement already satisfied: click-plugins>=1.0 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from fiona->geopandas) (1.1.1)
!pip install descartes
Requirement already satisfied: descartes in /srv/conda/envs/notebook/lib/python3.8/site-packages (1.1.0) Requirement already satisfied: matplotlib in /srv/conda/envs/notebook/lib/python3.8/site-packages (from descartes) (3.3.0) Requirement already satisfied: pillow>=6.2.0 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from matplotlib->descartes) (7.2.0) Requirement already satisfied: kiwisolver>=1.0.1 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from matplotlib->descartes) (1.2.0) Requirement already satisfied: python-dateutil>=2.1 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from matplotlib->descartes) (2.8.1) Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from matplotlib->descartes) (2.4.7) Requirement already satisfied: cycler>=0.10 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from matplotlib->descartes) (0.10.0) Requirement already satisfied: numpy>=1.15 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from matplotlib->descartes) (1.19.1) Requirement already satisfied: six>=1.5 in /srv/conda/envs/notebook/lib/python3.8/site-packages (from python-dateutil>=2.1->matplotlib->descartes) (1.15.0)

Downloading the Dataset

For the data analysis, we will be downloading the location data of populated areas in Sarawak state sourced from OpenStreetsMap and uploaded in Kaggle. The data contains different locations of settlements with its population, ranked by the local level of denomination; city, town, village etc.

import opendatasets as od
dataset_url = 'https://www.kaggle.com/azaleakamellia/sarawak-populated-areas-division'
od.download('https://www.kaggle.com/azaleakamellia/sarawak-populated-areas-division')