Plotting multiple countplots via a loop

Question

I have a pandas dataframe with different columns, one being year and another being doy. I would like to loop over the years (2001 to 2019) and plot the doy in different seaborn countplots for each year.

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

df = pd.read_csv("file.csv")
print(df.head())

        ID  doy    Year  ...  NA_L1NAME  B_year        number
1772  1774  199    2001  ...        1.1  1934.0  7.942371e+06
1786  1788  160    2002  ...        1.1  1953.0  2.146587e+05
1792  1794  199    2003  ...        1.2  1960.0  2.017792e+07
1801  1803  199    2004  ...        1.3  1968.0  4.293173e+05
1802  1804  195    2005  ...        1.4  1969.0  1.824599e+07

f, axes = plt.subplots(4,5)
for f,ax in zip(AKB.Year, axes.ravel()):
    sns.countplot(AKB.doy, ax = ax)
    ax.set_title(f)

However, this does not work.

How can I do it?

maybe you want a facet grid seaborn.pydata.org/generated/seaborn.FacetGrid.html — Chris
– Chris, Commented Dec 16, 2021 at 19:52

JohanC · Accepted Answer · 2021-12-16 20:50:41Z

1

You can use sns.catplot with kind='count' to create a FacetGrid of countplots:

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np

np.random.seed(2021)
df = pd.DataFrame({'year': np.repeat(np.arange(2001, 2020), 100)})
df['doi'] = np.random.randint(180, 200, len(df))

sns.catplot(data=df, kind='count', x='doi', col='year', col_wrap=5,
            height=3, aspect=1.8)
plt.tight_layout()
plt.show()

answered Dec 16, 2021 at 20:50

JohanC

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