Basics of Exploratory Data Analysis with the WHIN Dataset

This example is from TDM 102 Project 9 Spring 2024.

These example(s) depend on the database:

Learn more about the dataset here.

1aa. Use the method value_counts() to get the number of records for each station.

import pandas as pd
import time
s_t = time.time()
myDF = pd.read_csv('/anvil/projects/tdm/data/whin/weather.csv')
print(time.time()-s_t)

1.546401023864746

myDF['station_id'].value_counts()

import pandas as pd
import time
s_t = time.time()
myDF = pd.read_csv('/anvil/projects/tdm/data/whin/weather.csv')
print(time.time()-s_t)

1ab. Use the method groupby() to get the number of records for each station

myDF.groupby('station_id').size()