Rain in the US
Question
Suppose you have the following dataset, which contains information about a year's worth of US weather. Using Pandas, plot the top 10 locations that recieved the most rain in 2016. You will want to utilize the temperature field to flag when precipitation is rain (if it's too cold, the precipitation will be snow).
To help get you started, below is code to load the dataset into a Pandas dataframe. You can also make a copy of this Google Colab notebook.
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
data = pd.read_csv("https://raw.githubusercontent.com/erood/interviewqs.com_code_snippets/master/Datasets/weather.csv")
data.head()
| Data.Precipitation | Date.Full | Date.Month | Date.Week of | Date.Year | Station.City | ... | |
|---|---|---|---|---|---|---|---|
| 0 | 0.00 | 2016-01-03 | 1 | 3 | 2016 | Birmingham | ... |
| 1 | 0.00 | 2016-01-03 | 1 | 3 | 2016 | Huntsville | ... |
| 2 | 0.16 | 2016-01-03 | 1 | 3 | 2016 | Mobile | ... |
| 3 | 0.00 | 2016-01-03 | 1 | 3 | 2016 | Montgomery | ... |
| 4 | 0.01 | 2016-01-03 | 1 | 3 | 2016 | Anchorage | ... |