Visualizing harmful PM<sub>2.5</sub> levels in the US by county
# %pip install pandas geopandas folium matplotlib mapclassify import pandas as pd import geopandas as gpd import matplotlib.pyplot as plt # download the data from US NIH (https://hdpulse.nimhd.nih.gov/data-portal/physical/table?age=001&age_options=ageall_1&demo=234&demo_options=air_pollution_1&physicaltopic=002&physicaltopic_options=physical_2&race=00&race_options=raceall_1&sex=0&sex_options=sexboth_1&statefips=99&statefips_options=area_states) county_pm25: pd.DataFrame = pd.read_csv( "HDPulse_data_export.csv", skiprows=5, ) county_pm25
2025-12-06
Visualizing harmful PM<sub>2.5</sub> levels in the US by county
plotting fine particulate matters in the US
2024-12-08
Finding shadows in images using Python's scikit-image package
segmenting shadows in images using Python's scikit-image package
2024-03-05
Improved notebook to download buildings from Microsoft
download building footprints from Microsoft
2024-02-14
Scaling a Subset of Input Data in NetCDF Format
scaling a subset of data in a .nc file
2021-02-10
Regridding High-resolution Data
regridding geospatial data
2021-02-10
Regional Analysis Using R
R codes for matching gridded data with geographic information
2021-01-01
Python & R on Cheyenne/Casper
A simple guide to set up Jupyter on NCAR's supercomputers Cheyenne and Casper to use R and Python
2020-11-13
Oops! I did it again.
Hugo is just faster.
2020-10-12
This is the moment
So I have been told there is a new tool (new to me 😉) trending among academics. I was casually checking it out last night, and now, I have just finished my 12-hour journey of website migration. Not to bore you to death by giving you all the geeky 👓 and technical details (including how I googled and picked the nicest templates, extracted the good elements, studied their liquid syntax & HTML codes, reassembled them, fixed countless bugs, and ran numerous tests…), I will discuss some major advantages of Jekyll, as a static web page generator, over WordPress.
2020-10-09