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How Do I Use A For Loop And The Zip Function To Plot Subplots In Python?

- 1 answer

I'm new to python and stuck on using the zip function to plot subplots. Help is highly appreciated!!

I would like to plot bar charts for my nutrients in the dataframe, where I can distinguish between organic and non-organic. For each country in my dataframe I want subplots. This is my dataframe:

countryorganicnutrientsvalues
USFalsecarbohydrates45
USTruecarbohydrates41
DEFalsecalcium37
DETruecalcium31

And this is how my plot should look like: screenshot of expected plot

As I have many countries in my dataframe, I would like to us a for loop and the zip function. But i get an empty canvas when I implement this code:

fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(30, 15))

for i, ax in zip(range(0, 5), axes.flatten()):

    # Filter data for each country
    country_df = df[df["country"] == i]

    # Populate subplots
    ax.bar(country_df["nutrients"], country_df["values"], hue="organic")

    # Add x/y labels
    ax.set_xlabel("nutrients")
    ax.set_ylabel("average value")

Can somebody help? Thanks!!

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Answer

The problem with your code is when you try to filter by country, but you are actually filtering by a number (which will never match your plots). To easily create the grouping you show in the figure, I recommend using seaborn. A possible solution can be:

import seaborn as sns

countries = set(df['countries'])
# Calculate the number of subplots based on the number of countries
ncols = 3
nrows = math.ceil(len(countries) / ncols)
fig, axes = plt.subplots(nrows=nrows, ncols=ncols, figsize=(30, 15))

for country, ax in zip(countries, axes.flatten()):
    # Filter data for each country
    country_df = df[df["country"] == country]   # Select by country name

    # Populate subplots
    sns.barplot(data=country_df, x="nutrients", y="values", hue="organic", ax=ax)

    # Add x/y labels
    ax.set_xlabel("nutrients")
    ax.set_ylabel("average value")
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source: stackoverflow.com
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