Mutate charts

df1 = pd.DataFrame(
    np.random.randn(50, 20),
    columns=('col %d' % i for i in range(20)))

my_table = st.table(df1)

df2 = pd.DataFrame(
    np.random.randn(50, 20),
    columns=('col %d' % i for i in range(20)))

my_table.add_rows(df2)
# Now the table shown in the Streamlit app contains the data for
# df1 followed by the data for df2.

You can do the same thing with plots. For example, if you want to add more data to a line chart:

# Assuming df1 and df2 from the example above still exist...
my_chart = st.line_chart(df1)
my_chart.add_rows(df2)
# Now the chart shown in the Streamlit app contains the data for
# df1 followed by the data for df2.

And for plots whose datasets are named, you can pass the data with a keyword argument where the key is the name:

my_chart = st.vega_lite_chart({
     'mark': 'line',
     'encoding': {'x': 'a', 'y': 'b'},
     'datasets': {
       'some_fancy_name': df1,  # <-- named dataset
      },
     'data': {'name': 'some_fancy_name'},
 }),
my_chart.add_rows(some_fancy_name=df2)  # <-- name used as keyword