ccerv1’s gists

ccerv1 / clean_dates.py

Created April 26, 2019 05:22

Use strptime to standardize our date formats

	from datetime import datetime

	date_format = '%Y-%m-%dT%H:%M:%S'
	currency['Date'] = currency['DateTime'].apply(lambda x: datetime.strptime(x, date_format))
	inflation['Date'] = inflation['DateTime'].apply(lambda x: datetime.strptime(x, date_format))
	prices['Date'] = prices['DATE'].apply(lambda x: datetime.strptime(x, '%m/%d/%y'))

ccerv1 / load_real_prices_data.py

Created April 26, 2019 05:14

Ingests our three datasets for our price analysis

	import pandas as pd

	parent_url = 'https://raw.githubusercontent.com/numbers-coffee/blog/master/real_prices/'
	currency = pd.read_csv(parent_url + 'currency.csv')
	inflation = pd.read_csv(parent_url + 'inflation.csv')
	prices = pd.read_csv(parent_url + 'prices.csv')

ccerv1 / cagr_choropleth_v2.py

Created February 23, 2019 17:34

Pretty version of the CAGR choropleth map of coffee production

	growing_map = cagr_map[cagr_map.CAGR > 0]
	growing_map.plot(column='CAGR', cmap='YlGn', scheme='fisher_jenks', edgecolor='black', ax=ax)

	shrinking_map = cagr_map[cagr_map.CAGR < 0]
	shrinking_map.plot(column='CAGR', cmap='Reds_r', scheme='fisher_jenks', edgecolor='black', ax=ax)

	ax.set_ylim([-23.5,23.5])
	ax.set_xlim([-120,160])
	fig

ccerv1 / cagr_choropleth.py

Created February 23, 2019 13:49

V1 choropleth map of coffee production growth rates

	cagr_map = pd.concat([world_map, world_production], axis=1, sort=True)
	cagr_map.fillna(0, inplace=True)
	cagr_map.plot(column='CAGR', cmap='Blues')

ccerv1 / world_production_cagr.py

Created February 23, 2019 13:43

Apply a CAGR function to each country's production series

	def cagr(series):
	start_val = series.iloc[0]
	if not start_val:
	return None
	end_val = series.iloc[-1]
	num_vals = len(series)
	CAGR = (end_val/start_val)**(1/num_vals)-1
	return CAGR

	world_production['CAGR'] = world_production.apply(cagr, axis=1)

ccerv1 / country_rename.py

Created February 23, 2019 13:30

Rename country indices that have alternative spellings

	world_production.rename({
	"Cote d'Ivoire": "Côte d'Ivoire",
	"Central African Republic": "Central African Rep.",
	"Congo (Kinshasa)": "Dem. Rep. Congo",
	"Dominican Republic": "Dominican Rep.",
	"Laos": "Lao PDR"
	}, inplace=True)

ccerv1 / world_production.py

Created February 23, 2019 13:21

Extract world production over the last 25 years from USDA table

	world_production = attribute_query('Production')
	world_production.fillna(0,inplace=True)
	world_production = world_production.iloc[:,-YEARS_IN_SERIES:]

ccerv1 / pretty_world_map.py

Created February 23, 2019 13:16

Pretty version of the GeoPandas world map

	fig, ax = plt.subplots(figsize=(20,8))
	ax.set_aspect('equal')
	world_map.plot(color='#f2f2f2', edgecolor="Grey", ax=ax)

ccerv1 / world_map.py

Created February 23, 2019 13:14

Create a new table with relevant features only

	world_map = world[world.name != 'Antarctica']
	world_map = world_map[['name', 'geometry']]
	world_map.set_index('name', inplace=True)

ccerv1 / geopandas_basemap.py

Created February 23, 2019 12:48

Display the default GeoPandas base map of the world

	import geopandas
	world = geopandas.read_file(geopandas.datasets.get_path('naturalearth_lowres'))
	world.plot()

Carl Cervone ccerv1