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Update app.py
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app.py
CHANGED
@@ -55,7 +55,7 @@ if query:
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print("Similarity to " + str(query))
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pd.set_option('display.max_rows', None)
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print(table.head(50))
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table.head(10).to_csv("clotting_sim1.csv", index=True)
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# short_table = table.head(50)
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# print(table)
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st.subheader(f"Similar Words to {query}")
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@@ -79,6 +79,13 @@ if query:
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st.pyplot(fig)
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plt.clf()
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# st.write(short_table)
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#
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@@ -92,13 +99,13 @@ if query:
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df1["Human Gene"] = df1["Human Gene"].str.upper()
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print(df1.head(50))
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print()
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df1.head(50).to_csv("clotting_sim2.csv", index=True, header=False)
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# time.sleep(2)
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st.subheader(f"Similar Genes to {query}")
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sizes =
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cmap2 = plt.cm.Blues(np.linspace(0.05, .5, len(sizes)))
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color2 = [cmap2[i] for i in range(len(sizes))]
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@@ -116,6 +123,13 @@ if query:
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# # display the treemap in Streamlit
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st.pyplot(fig2)
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print("Similarity to " + str(query))
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pd.set_option('display.max_rows', None)
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print(table.head(50))
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# table.head(10).to_csv("clotting_sim1.csv", index=True)
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# short_table = table.head(50)
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# print(table)
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st.subheader(f"Similar Words to {query}")
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st.pyplot(fig)
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plt.clf()
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csv = table.head(100)
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st.download_button(
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label="download top 100 words (csv)",
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data=csv,
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file_name='clotting_words.csv',
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mime='text/csv')
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# st.write(short_table)
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#
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df1["Human Gene"] = df1["Human Gene"].str.upper()
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print(df1.head(50))
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print()
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# df1.head(50).to_csv("clotting_sim2.csv", index=True, header=False)
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# time.sleep(2)
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st.subheader(f"Similar Genes to {query}")
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df10 = df1.head(10)
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df10.index = 1/df10.index
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sizes = df10.index.tolist()
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cmap2 = plt.cm.Blues(np.linspace(0.05, .5, len(sizes)))
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color2 = [cmap2[i] for i in range(len(sizes))]
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# # display the treemap in Streamlit
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st.pyplot(fig2)
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csv = df1.head(100)
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st.download_button(
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label="download top 100 genes (csv)",
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data=csv,
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file_name='clotting_genes.csv',
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mime='text/csv')
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