Animate and update elements
Sometimes you display a chart or dataframe and want to modify it live as the app runs (for example, in a loop). Some elements have built-in methods to allow you to update them in-place without rerunning the app.
Updatable elements include the following:
st.emptycontainers can be written to in sequence and will always show the last thing written. They can also be cleared with an additional.empty()called like a method.st.dataframe,st.table, and many chart elements can be updated with the.add_rows()method which appends data.st.progresselements can be updated with additional.progress()calls. They can also be cleared with a.empty()method call.st.statuscontainers have an.update()method to change their labels, expanded state, and status.st.toastmessages can be updated in place with additional.toast()calls.
st.empty containers
st.empty can hold a single element. When you write any element to an st.empty container, Streamlit discards its previous content
displays the new element. You can also st.empty containers by calling .empty() as a method. If you want to update a set of elements, use
a plain container (st.container()) inside st.empty and write contents to the plain container. Rewrite the plain container and its
contents as often as desired to update your app's display.
The .add_rows() method
st.dataframe, st.table, and all chart functions can be mutated using the .add_rows() method on their output. In the following example, we use my_data_element = st.line_chart(df). You can try the example with st.table, st.dataframe, and most of the other simple charts by just swapping out st.line_chart. Note that st.dataframe only shows the first ten rows by default and enables scrolling for additional rows. This means adding rows is not as visually apparent as it is with st.table or the chart elements.
import streamlit as st
import pandas as pd
import numpy as np
import time
df = pd.DataFrame(np.random.randn(15, 3), columns=(["A", "B", "C"]))
my_data_element = st.line_chart(df)
for tick in range(10):
time.sleep(.5)
add_df = pd.DataFrame(np.random.randn(1, 3), columns=(["A", "B", "C"]))
my_data_element.add_rows(add_df)
st.button("Regenerate")
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