Assignment 5b: Pandas Groupby with Hurricane Data

Assignment 5b: Pandas Groupby with Hurricane Data#

At-home assignment — worth 10 points. When you’re done, push your work to your week folder and post a link to your completed notebook on the matching Courseworks assignment.

In this assignment you’ll apply groupby and time-series operations to the NOAA IBTrACS hurricane dataset.

Learning goals

This assignment exercises the groupby and time-series skills from this section:

  • Read a large CSV file with custom column-type handling

  • Rename columns and inspect unique values

  • Filter and nlargest operations on a DataFrame

  • Use groupby to count, aggregate, and iterate over groups

  • Plot scatter plots, bar charts, and hexbin plots from a DataFrame

  • Set a datetime index and use it for time-based filtering

  • Compute climatologies and anomalies with groupby + transform

Working through this notebook

Download this notebook using the ⬇ button in the top-right (or copy-paste the cells into a fresh notebook), open it in your environment (JupyterLab on LEAP or Colab), and fill in your solution under each numbered task.

When you’re done, follow the submission instructions at the bottom of the page.

Start by importing numpy, pandas, and matplotlib’s pyplot. The cell below is empty — type your imports there and run it.

Use the following code to load a CSV file of the NOAA IBTrACS hurricane dataset:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

url = 'https://www.ncei.noaa.gov/data/international-best-track-archive-for-climate-stewardship-ibtracs/v04r00/access/csv/ibtracs.ALL.list.v04r00.csv'
df = pd.read_csv(url, parse_dates=['ISO_TIME'], usecols=range(12),
                 skiprows=[1], na_values=[' ', 'NOT_NAMED'],
                 keep_default_na=False, dtype={'NAME': str})
df.head()

Basin Key: (NI - North Indian, SI - South Indian, WP - Western Pacific, SP - Southern Pacific, EP - Eastern Pacific, NA - North Atlantic)

How many rows does this dataset have?

len(df)

How many North Atlantic hurricanes are in this dataset?

1) Get the unique values of the BASIN, SUBBASIN, and NATURE columns#

2) Rename the WMO_WIND and WMO_PRES columns to WIND and PRES#

3) Get the 10 largest rows in the dataset by WIND#

You will notice some names are repeated.

4) Group the data on SID and get the 10 largest hurricanes by WIND#

5) Make a bar chart of the wind speed of the 20 strongest-wind hurricanes#

Use the name on the x-axis.

6) Plot the count of all datapoints by Basin#

as a bar chart

7) Plot the count of unique hurricanes by Basin#

as a bar chart.

8) Make a hexbin of the location of datapoints in Latitude and Longitude#

9) Find Hurricane Katrina (from 2005) and plot its track as a scatter plot#

First find the SID of this hurricane.

Next get this hurricane’s group and plot its position as a scatter plot. Use wind speed to color the points.

10) Make time the index on your dataframe#

11) Plot the count of all datapoints per year as a timeseries#

You should use resample

12) Plot all tracks from the North Atlantic in 2005#

You will probably have to iterate through a GroupBy object

13) Create a filtered dataframe that contains only data since 1970 from the North Atlantic (“NA”) Basin#

Use this for the rest of the assignment

14) Plot the number of datapoints per day from this filtered dataframe#

Make sure you figure is big enough to actually see the plot

15) Calculate the climatology of datapoint counts as a function of dayofyear#

Plot the mean and standard deviation on a single figure

16) Use transform to calculate the anomaly of daily counts from the climatology#

Resample the anomaly timeseries at annual resolution and plot a line with dots as markers.

Which years stand out as having anomalous hurricane activity?

Submission instructions#

When you’re done, save your completed notebook as assignment5b.ipynb inside the current week’s folder in your private clmt5405-assignments GitHub repo. Then push the commit:

git add <weekN>/assignment5b.ipynb
git commit -m "Submit assignment 5b"
git push

Due Sunday night.