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You are reading the documentation for Streamlit in Snowflake. For open-source Streamlit, version 1.41.0 is the latest version available.

  1. Contents
  2. st.bar_chart
  3. element.add_rows

st.bar_chart

Display a bar chart.

This is just syntax-sugar around st.altair_chart. The main difference is this command uses the data's own column and indices to figure out the chart's spec. As a result this is easier to use for many "just plot this" scenarios, while being less customizable.

If st.bar_chart does not guess the data specification correctly, try specifying your desired chart using st.altair_chart.

Function signature[source]

st.bar_chart(data=None, *, x=None, y=None, width=0, height=0, use_container_width=True)

Parameters

data (pandas.DataFrame, pandas.Styler, pyarrow.Table, numpy.ndarray, pyspark.sql.DataFrame, snowflake.snowpark.dataframe.DataFrame, snowflake.snowpark.table.Table, Iterable, or dict)

Data to be plotted. 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".

x (str or None)

Column name to use for the x-axis. If None, uses the data index for the x-axis. This argument can only be supplied by keyword.

y (str, sequence of str, or None)

Column name(s) to use for the y-axis. If a sequence of strings, draws several series on the same chart by melting your wide-format table into a long-format table behind the scenes. If None, draws the data of all remaining columns as data series. This argument can only be supplied by keyword.

width (int)

The chart width in pixels. If 0, selects the width automatically. This argument can only be supplied by keyword.

height (int)

The chart height in pixels. If 0, selects the height automatically. This argument can only be supplied by keyword.

use_container_width (bool)

If True, set the chart width to the column width. This takes precedence over the width argument. This argument can only be supplied by keyword.

Example

import streamlit as st
import pandas as pd
import numpy as np

chart_data = pd.DataFrame(
    np.random.randn(20, 3),
    columns=["a", "b", "c"])

st.bar_chart(chart_data)
Built with Streamlit 🎈

element.add_rows

Concatenate a dataframe to the bottom of the current one.

Function signature[source]

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

Parameters

data (pandas.DataFrame, pandas.Styler, pyarrow.Table, numpy.ndarray, pyspark.sql.DataFrame, snowflake.snowpark.dataframe.DataFrame, 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

import streamlit as st
import pandas as pd
import numpy as np

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
Previous: st.area_chartNext: st.line_chart
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