Data Case Study 1

Data Case Study 1#

Take a look at the landing page for the dataset:
Snowpack, precipitation, and temperature measurements at the Central Sierra Snow Laboratory for water years 1970 to 2019
https://doi.org/10.6078/D1941T

dryad snow

With the information shown above, and using the link provided, answer the following questions:

Background#

Questions#

  1. Why was the data collected?

  2. What are the limitations of the data?

Publisher / Host#

Questions

  1. Where is the data hosted? (What is the name of the repository?)

  2. Is there a theme or subject focus to the repository?

  3. What other types of data would you expect to find there?

Citation#

Questions

  1. How would you cite the data?

  2. Is there an example or recommendation?

Answer

Osterhuber, Randall; Schwartz, Andrew (2021), Snowpack, precipitation, and temperature measurements at the Central Sierra Snow Laboratory for water years 1971 to 2019, Dryad, Dataset, https://doi.org/10.6078/D1941T

Licensing#

Questions

  1. Are you allowed to reuse this dataset?

  2. How do you know?

Answer

License Example

Data#

Take a look at Whole_WY_1980.csv, one of the 49 data files.

Questions#

  • How many rows of data are there? Why?

  • What’s a Water Year? Can you tell when a Water Year starts?

  • When was the first snowfall of the 1979-1980 Water Year?

# Read in the data file from the 1980 water year

import pandas as pd

snow_data_1980 = pd.read_csv('./data/Whole_WY_1980.csv')
snow_data_1980
Date Air Temp Max (C) Air Temp Min (C) 24-hour Total Precip (mm) Season Total Precip (mm) % of Precip as Snow % of Precip as Rain New Snow (cm) Season Total Snow (cm) Snowpack depth (cm) Snow Water Equivalent (cm) Remarks
0 1979-10-01 23.31 8.88 0 0.000 -- -- 0 0.0 0 0 NaN
1 1979-10-02 22.755 6.66 0 0.000 NaN NaN 0 0.0 0 0 changed charge
2 1979-10-03 23.31 6.66 0 0.000 NaN NaN 0 0.0 0 0 NaN
3 1979-10-04 23.31 5.55 0 0.000 NaN NaN 0 0.0 0 0 NaN
4 1979-10-05 22.755 4.995 0 0.000 NaN NaN 0 0.0 0 0 NaN
... ... ... ... ... ... ... ... ... ... ... ... ...
361 1980-09-26 21.09 4.44 0 1968.794 NaN NaN 0 1083.3 0 0 NaN
362 1980-09-27 20.535 2.775 0 1968.794 NaN NaN 0 1083.3 0 0 NaN
363 1980-09-28 23.31 0.555 0 1968.794 NaN NaN 0 1083.3 0 0 NaN
364 1980-09-29 25.53 6.105 0 1968.794 NaN NaN 0 1083.3 0 0 NaN
365 1980-09-30 27.195 4.44 0 1968.794 NaN NaN 0 1083.3 0 0 NaN

366 rows × 12 columns

Plot#

What if you plotted the data? What could you see?

import matplotlib.pyplot as plt

snow_data_1980.plot(x='Date', y='Season Total Snow (cm)')
plt.xticks(rotation = 45)
plt.show()
../_images/54aad6e9012bf86342e152ebb3c0c55ebc0a06475257433b31077f32418f0de1.png

Final Thoughts

What other questions could you explore with this data?

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