Out: 10/25 19:00
Due: 11/08 19:00
Collaboration:
Collaboration on solving the assignment is allowed, after you have thought about the problem sets on your own. It is also OK to get clarification (but not solutions) from online resources, again after you have thought about the problem sets on your own.
There are two requirements about collaboration:
Cite your collaborators fully and completely (e.g., “XXX explained to me what is asked in problem set 3”). Or cite online resources (e.g., “I got inspired by reading XXX”) that helped you.
Write your scripts and report independently - the scripts and report must come from you only.
Submitting your assignment:
Please write a report PS2.pdf.
Create a jupyter notebook named PS2.ipynb.
Upload your jupyter notebook and report to your
Github ESE5023_Assignments_XXX repository (where
XXX is your SUSTech ID) before the due time.
Late Submission:
Late submissions will not receive any credit. The submission time will be determined based on your latest GitHub file records.
The Significant
Earthquake Database contains information on destructive earthquakes
from 2150 B.C. to the present. On the top left corner, select all
columns and download the entire significant earthquake data file in
.tsv format by clicking the Download TSV File
button. Click the variable name for more information. Read the file
(e.g., earthquakes-2023-10-24_16-20-01_+0800.tsv) as an
object and name it Sig_Eqs.
1.1 [5 points] Compute the total number of deaths caused by earthquakes since 2150 B.C. in each country, and then print the top ten countries along with the total number of deaths.
1.2 [10 points] Compute the total number of
earthquakes with magnitude larger than 6.0 (use column
Mag as the magnitude) worldwide each year, and then plot
the time series. Do you observe any trend? Explain why or why not?
1.3 [10 points] Write a function
CountEq_LargestEq that returns both (1) the total number of
earthquakes since 2150 B.C. in a given country AND (2) the date of the
largest earthquake ever happened in this country. Apply
CountEq_LargestEq to every country in the file, report your
results in a descending order.
In this problem set, we will examine how wind speed changes in
Shenzhen during the past 10 years, we will take a look at
the hourly weather data measured at the BaoAn International Airport. The
data set is from NOAA
Integrated Surface Dataset. Download the file 2281305.zip,
where the number 2281305 is the site ID. Extract the zip
file, you should see a file named 2281305.csv. Save the
.csv file to your working directory.
Read page 8-9 (POS 65-69 and
POS 70-70) of the comprehensive user
guide for the detailed format of the wind data. Explain how you
filter the data in your report.
[10 points] Plot monthly averaged wind speed as a
function of the observation time. Is there a trend in monthly averaged
wind speed within the past 10 years?
Browse the CASEarth, National Centers for Environmental
Information (NCEI), or Advanced
Global Atmospheric Gases Experiment (AGAGE) website. Search and
download a data set you are interested in. You are also welcome to use
data from your group in this problem set. But the data set should be in
csv, XLS, or XLSX format, and
have temporal information.
3.1 [5 points] Load the csv,
XLS, or XLSX file, and clean possible data
points with missing values or bad quality.
3.2 [5 points] Plot the time series of a certain variable.
3.3 [5 points] Conduct at least 5
simple statistical checks with the variable, and report your
findings.