如何使用 pandas / geopandas 增加 plot 的 bin 数量？

Question

Currently a lot of my data is showing with a huge range of values in one bin - all data goes from 0 to 1.31, but my top bin colour is holding 0.15 to 1.31.

This is my code to plot:

merged.plot(column='vaccinations_per_person', scheme="quantiles", figsize=(25, 20),
           legend=True, norm=colour, cmap='Oranges', missing_kwds = 
           dict(color = "lightgrey", label = "No Data"))
plt.title('Vaccinations per Person',fontsize=25)

And this is my legend:

Answer 1

You can do it easily by specifying the number of bins as k=10 (if you want 10).

 merged.plot(column='vaccinations_per_person', scheme="quantiles", figsize=(25, 20),
           legend=True, norm=colour, cmap='Oranges', missing_kwds = 
           dict(color = "lightgrey", label = "No Data"), k=10)

Answer 2

• use a colormap with scatter and there is no limit to bins

import pandas as pd
import io, requests, matplotlib

dfraw = pd.read_csv(io.StringIO(requests.get("https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/vaccinations/vaccinations.csv").text))

cmap = matplotlib.colors.LinearSegmentedColormap.from_list("", ["aqua","limegreen","green"])

dfraw["date"] = pd.to_datetime(dfraw["date"])
dfp = (dfraw.sort_values(["iso_code","date"])
 .groupby(["iso_code"], as_index=False).last()
 .loc[:,["iso_code","people_vaccinated_per_hundred"]]
 .dropna()
 .plot(kind="scatter", x="iso_code", y="people_vaccinated_per_hundred", c="people_vaccinated_per_hundred", cmap=cmap)
)

Using geopandas and folium with the same colormap and a bit more preparation you get to: