Here's the code to print the number of missing values in `banking`, visualize the missingness matrix, and print the number of missing values by column:
```python
import missingno as msno
# Print number of missing values in banking
print(banking.isnull().sum())
# Visualize missingness matrix
msno.matrix(banking)
# Print number of missing values by column
print(banking.isnull().sum(axis=0))
```
In this code, we first import the `missingno` library using the `import` statement.
We then use the `isnull()` function to check for missing values in the `banking` DataFrame, and the `sum()` function to count the number of missing values. We use the `print()` function to display the result.
We use the `msno.matrix()` function from the `missingno` library to plot and show the missingness matrix of the `banking` DataFrame.
Finally, we use the `isnull()` function again, but this time with the `axis=0` parameter to count the number of missing values by column. We use the `print()` function to display the result.