Mutate charts

Sometimes you display a chart or dataframe and want to modify live as the app runs (for example, in a loop). Depending on what you're looking for, there are 3 different ways to do this:

  1. Using st.empty to replace a single element.
  2. Using st.container or st.columns to replace multiple elements.
  3. Using add_rows to append data to specific types of elements.

Here we discuss that last case.

Concatenate a dataframe to the bottom of the current one.
Function signature

element.add_rows(self, data=None, **kwargs)

Parameters

data (pandas.DataFrame, pandas.Styler, pyarrow.Table, numpy.ndarray, Iterable, dict, or None)

Table to concat. Optional. Pyarrow tables are not supported by Streamlit's legacy DataFrame serialization (i.e. with config.dataFrameSerialization = "legacy"). To use pyarrow tables, please enable pyarrow by changing the config setting, config.dataFrameSerialization = "arrow".

**kwargs (pandas.DataFrame, numpy.ndarray, Iterable, dict, or None)

The named dataset to concat. Optional. You can only pass in 1 dataset (including the one in the data parameter).

Example

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

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