streamlit

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# Copyright (c) Streamlit Inc. (2018-2022) Snowflake Inc. (2022-2024)
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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#     http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import numpy as np
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import pandas as pd
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import streamlit as st
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from tests.streamlit import snowpark_mocks
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# Explicitly seed the RNG for deterministic results
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np.random.seed(0)
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data = np.random.randn(100, 100)
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df = pd.DataFrame(data)
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st.dataframe(df)
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st.dataframe(df, 250, 150)
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st.dataframe(df, width=250)
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st.dataframe(df, height=150)
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st.dataframe(df, 5000, 5000)
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st.dataframe(df, use_container_width=True)
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small_df = pd.DataFrame(np.random.randn(100, 3))
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st.dataframe(small_df, width=500)
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st.dataframe(small_df, use_container_width=True)
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st.dataframe(small_df, width=200, use_container_width=True)
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st.dataframe(small_df, width=200, use_container_width=False)
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one_col_df = pd.DataFrame(np.random.randn(100, 1))
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st.dataframe(one_col_df, use_container_width=True)
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st.dataframe(snowpark_mocks.DataFrame(), use_container_width=True)
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