Create for loop to plot histograms for individual columns of DataFrame with Seaborn

Question

So I'm trying to plot histograms for all my continous variables in my DatFrame using a for loop I've already managed to do this for my categorical variables using countplot with the following code:

df1 = df.select_dtypes([np.object])

for i, col in enumerate(df1.columns):
    plt.figure(i)
    sns.countplot(x=col, data=df1)

Which I found here by searching SO.

However now I want to do the same with distplot so I tried modifying the above code to:

df1 = dftest.select_dtypes([np.int, np.float])

for i, col in enumerate(df1.columns):
    plt.figure(i)
    sns.distplot(df1)

But it just gived me one empty plot. Any ideas on what I can do?

edit: e.g of DataFrame:

dftest = pd.DataFrame(np.random.randint(low=0, high=10, size=(5, 5)),
                    columns=['a', 'b', 'c', 'd', 'e']) 

Answer 1

sns.distplot has been replaced by sns.histplot. See Emulating deprecated seaborn distplots to match distplot.

for i, col in enumerate(df1.columns):
    plt.figure(i)
    sns.histplot(df1[col], stat='density', kde=True, kde_kws={"cut": 3})

---

It seems like you want to produce one figure with a distplot per column of the dataframe. Hence you need to specify the data in use for each specific figure.

As the seaborn documentation says for distplot(a, ...)

a : Series, 1d-array, or list. Observed data.

So in this case:

for i, col in enumerate(df1.columns):
    plt.figure(i)
    sns.distplot(df1[col])