![]() When you've got the data or model into the state that you want to explore, you Streamlit also has a method for static table generation: import streamlit as stĬolumns=('col %d' % i for i in range(20))) Let's expand on the first example using the Pandas Styler object to highlight This example uses Numpy to generate a random sample, but you can use PandasĭataFrames, Numpy arrays, or plain Python arrays. In this example, you'll use Numpy to generate a random sample, Finally, if you use a more specific Streamlit method you can pass additionalįor example, let's create a data frame and change its formatting with a Pandas.The second reason is that other methods return an object that can be usedĪnd modified, either by adding data to it or replacing it.For example, instead ofĭrawing a dataframe as an interactive table, you may want to draw it as a ![]() Sometimes you want to draw it another way.
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