rename
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@@ -138,7 +138,7 @@ def _(WORKING_DIR, all_tags_df, mo, tag_select):
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# filter all_tags_df to only the document = file_dropdown.value
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tags_df = all_tags_df.loc[all_tags_df['tag'] == tag_select.value].copy()
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tags_df
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tags_df.head()
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return (
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KEYWORDS_FPATH,
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KEYWORD_FREQ_FPATH,
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@@ -150,9 +150,9 @@ def _(WORKING_DIR, all_tags_df, mo, tag_select):
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@app.cell(hide_code=True)
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def _(mo):
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mo.md(r"""
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# 4) Keyword extraction
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def _(KEYWORD_FREQ_FPATH, mo):
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mo.md(rf"""
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# 4) Keyword extraction {'(skippable, see 4b)' if KEYWORD_FREQ_FPATH.exists() else ''}
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""")
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return
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@@ -267,7 +267,7 @@ def _(KEYWORD_FREQ_FPATH, mo, start_processing_btn):
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load_existing_btn = None
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if KEYWORD_FREQ_FPATH.exists():
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load_existing_btn = mo.ui.run_button(label=f"Load keywords from `{KEYWORD_FREQ_FPATH.name}`")
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load_existing_btn = mo.ui.run_button(label=f"Load keywords from `{KEYWORD_FREQ_FPATH.name}`", kind='warn')
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load_existing_btn
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return (load_existing_btn,)
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@@ -349,7 +349,7 @@ def _(mo, tag_select):
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return
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@app.cell
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@app.cell(hide_code=True)
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def _(frequency_df, min_freq_select, mo):
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mo.stop('keyword' not in frequency_df.columns, "Waiting for keyword extraction to finish")
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@@ -384,7 +384,7 @@ def _(KEYWORD_FREQ_FPATH, frequency_df, mo, remove_rows_btn, table_selection):
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try:
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frequency_df.drop(index=rows_to_drop, inplace=True, axis=0)
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except KeyError:
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_s = mo.callout("GO TO STEP 4b) and reload data to continue refining the dataset.", kind='warn')
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_s = mo.callout("GO BACK TO STEP 4b) and reload data to continue refining the dataset.", kind='warn')
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else:
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# Save updated frequencies back to xlsx
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frequency_df.to_excel(
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@@ -395,7 +395,7 @@ def _(KEYWORD_FREQ_FPATH, frequency_df, mo, remove_rows_btn, table_selection):
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print(f"Updated keyword frequencies saved to: `{KEYWORD_FREQ_FPATH}`")
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# mo.callout(f"Updated keyword frequencies saved to: `{KEYWORD_FREQ_FPATH}`", kind="success")
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_s = mo.callout("GO TO STEP 4b) and reload data to continue refining the dataset.", kind='warn')
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_s = mo.callout("GO BACK TO STEP 4b) and reload data to continue refining the dataset.", kind='warn')
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_s
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return
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@@ -436,11 +436,13 @@ def _(mo):
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canvas_size = (1200, 800)
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logo_switch = mo.ui.switch(label="Include Chase Logo", value=False)
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return buffer, canvas_size, logo_switch
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n_words = mo.ui.slider(start=10, stop=200, step=1, value=40, debounce=True, show_value=True, label="Max number of words in WordCloud")
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return buffer, canvas_size, logo_switch, n_words
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@app.cell(hide_code=True)
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def _(logo_switch, mo):
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def _(logo_switch, mo, n_words):
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run_wordcloud_btn = mo.ui.run_button(label="Generate WordCloud")
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mo.vstack([
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@@ -451,7 +453,7 @@ def _(logo_switch, mo):
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When satisfied with the result, click 'Save WordCloud to File' to save the image."""),
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mo.md('---'),
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mo.hstack([logo_switch, run_wordcloud_btn], align='center', justify='space-around')]
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mo.hstack([logo_switch, n_words, run_wordcloud_btn], align='center', justify='space-around')]
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)
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return (run_wordcloud_btn,)
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@@ -469,6 +471,7 @@ def _(
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frequency_df,
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logo_switch,
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mo,
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n_words,
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np,
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plt,
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run_wordcloud_btn,
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@@ -532,7 +535,7 @@ def _(
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width=canvas_size[0],
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height=canvas_size[1],
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max_font_size=100, # Increased font size for larger canvas
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max_words=40, # Increased word count to fill space
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max_words=n_words.value, # Increased word count to fill space
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color_func=blue_color_func,
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mask=chase_mask, # Apply the circular mask
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contour_width=0,
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@@ -546,7 +549,7 @@ def _(
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width=canvas_size[0],
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height=canvas_size[1],
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max_font_size=150, # Increased font size for larger canvas
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max_words=40, # Increased word count to fill space
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max_words=n_words.value, # Increased word count to fill space
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color_func=blue_color_func,
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# mask=chase_mask, # Apply the circular mask
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# contour_width=0,
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