Figure1-Plot.ipynb
: plot Figure 1 in Python
Figure2-Spatial analysis by R.ipynb
: spatial analysis of the spread of COVID-19 in R
Figure2-Spatial analysis and plot.ipynb
: spatial analysis of the spread of COVID-19 and plot Figure 2 in Python
Figure3-Outbreak analysis by R.ipynb
: outbreak analysis of the spread of COVID-19 in R
Figure3-Plot.ipynb
: plot Figure 3 in Python
Figure4-Plot.ipynb
: plot Figure 4 in Python
To execute the tutorial, make sure you have Python 3, R/R-Studio and Jupyter notebook installed.
To run R script in Jupyter, IRkernel is required. This package is available on CRAN and you can install it in R/R-Studio Console by:
install.packages('IRkernel')
IRkernel::installspec() # register the kernel in the current R installation
os
numpy
pandas
itertools
seaborn
matplotlib
statsmodels
collections
readr
MASS
dplyr
tidyr
texreg
The spatial dissemination of COVID-19 and associated socio-economic consequences.
https://royalsocietypublishing.org/doi/10.1098/rsif.2021.0662
Yafei Zhang, Lin Wang, Jonathan J. H. Zhu, Xiaofan Wang
Journal of the Royal Society Interface, 19(187), 20210662 (2022).
@article{Zhang2022,
author = {Zhang, Yafei and Wang, Lin and Zhu, Jonathan J. H. and Wang, Xiaofan},
title = {The spatial dissemination of COVID-19 and associated socio-economic consequences},
journal = {Journal of The Royal Society Interface},
volume = {19},
number = {187},
pages = {20210662},
year = {2022},
doi = {10.1098/rsif.2021.0662},
URL = {https://royalsocietypublishing.org/doi/abs/10.1098/rsif.2021.0662},
eprint = {https://royalsocietypublishing.org/doi/pdf/10.1098/rsif.2021.0662},
}
Should you have any further quires about the code and data, please contact at: yflyzhang_at_gmail.com