How to avoid empty grids in seaborn FacetGrid

Question

I have a dataframe of personal characteristics like school grades, age, weight, and height. I want to investigate the density distribution of these data within a seaborn Facetgrid.

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

# creation of artifical data
random.seed = 10
high = [random.uniform(3.0,6.0) for i in range(50)]
uni = [random.uniform(1.0, 4.0) for i in range(50)]
math = [random.uniform(1.0, 6.0) for i in range(50)]
bio = [random.uniform(1.0, 6.0) for i in range(50)]
history = [random.uniform(1.0, 6.0) for i in range(50)]
age = [random.randint(15,45) for i in range(50)]
height = [random.randint(150,210) for i in range(50)]
weight = [random.randint(50,100) for i in range(50)]

df = pd.DataFrame()
df["value"] = high + uni + math + bio + history + age + height + weight
df["type"] = 100*["final_exam"] + 150*["grade"] + 150*["body"]
df["id"] = 50*["highschool"] + 50*["university"] + 50*["math"] + 50*["bio"]    + 50*["history"] + 50*["age"] + 50*["heigt"] + 50*["weight"]
df["group"] = "A"
df = df[["group", "id", "type", "value"]]
df["para"] =df[["type", "id"]].apply(lambda x: "_".join(x), axis=1)


# Plotting function
def plot_poll(df, **kwargs):

    def plot_densitiy_distribution(data, **kwargs):
        sns.kdeplot(data["value"], shade=True)

    grid_ts = sns.FacetGrid(df, sharey=False, legend_out=True,    hue="group",col="type", row="id")
    grid_ts = grid_ts.map_dataframe(plot_densitiy_distribution)
    plt.tight_layout()
    plt.show()

# main
plot_poll(df)   

The dataframe will look like this for a single person but in total 50 persons were interviewed:

+=======+============+============+=======+=======================+  
| group |     id     |    type    | value |          para         |
+=======+============+============+=======+=======================+   
|   A   | highschool | final_exam |  2.7  | final_exam_highschool |
+-------+------------+------------+-------+-----------------------+
|   A   | university | final_exam |  2.0  | final_exam_university |
+-------+------------+------------+-------+-----------------------+
|   A   |    math    |    grade   |  3.3  |     grade_math        |
+-------+------------+------------+-------+-----------------------+
   ..............................................................
+-------+------------+------------+-------+-----------------------+
|   A   |    age     |    body    |  27   |        body_age       |
+-------+------------+------------+-------+-----------------------+
   ..............................................................
+=======+============+============+=======+=======================+

The figure looks like this:

As you can see, there a lot of empty plots and I would like to rearrange the plot that only grids with data are present. In the columns grids should be shown that have the same type. An example (created with Paint) can be seen below. Furthermore the x-axis is scaled equally for all columns. How can I scale the x-axis individually (even maybe logarithmic).

rearranged figure (with Paint)

Thanks in advance for your support, Christian

Answer 1

If you just want to hide plots for presentation purpose (but keep the overall grid structure):

    for (i,j,k), data in fg.facet_data():
        if data.empty:
            ax = fg.facet_axis(i, j)
            ax.set_axis_off()