prashant
commited on
Commit
•
62fb673
1
Parent(s):
f9b5e7f
pie chart fix
Browse files- appStore/sdg_analysis.py +6 -3
- utils/sdg_classifier.py +1 -0
appStore/sdg_analysis.py
CHANGED
@@ -129,16 +129,18 @@ def app():
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fig, ax = plt.subplots()
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ax.pie(x['count'], colors=colors, radius=2, center=(4, 4),
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wedgeprops={"linewidth": 1, "edgecolor": "white"},
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-
frame=False,labels =list(x.
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# fig.savefig('temp.png', bbox_inches='tight',dpi= 100)
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st.markdown("#### Anything related to SDGs? ####")
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c4, c5, c6 = st.columns([
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with c5:
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st.pyplot(fig)
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st.markdown("###### What keywords are present under SDG classified text? ######")
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@@ -147,7 +149,8 @@ def app():
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# st.table(tRkeywordsDf)
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AgGrid(tRkeywordsDf, reload_data = False,
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update_mode="value_changed",
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-
columns_auto_size_mode = ColumnsAutoSizeMode.FIT_CONTENTS
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st.markdown("###### Top few SDG Classified paragraph/text results ######")
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# c7, c8, c9 = st.columns([1, 10, 1])
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fig, ax = plt.subplots()
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ax.pie(x['count'], colors=colors, radius=2, center=(4, 4),
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wedgeprops={"linewidth": 1, "edgecolor": "white"},
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+
frame=False,labels =list(x.SDG))
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# fig.savefig('temp.png', bbox_inches='tight',dpi= 100)
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st.markdown("#### Anything related to SDGs? ####")
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+
c4, c5, c6 = st.columns([1, 5, 2])
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with c5:
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st.pyplot(fig)
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with c6:
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st.table(x[['SDG','SDG_name']])
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st.markdown("###### What keywords are present under SDG classified text? ######")
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# st.table(tRkeywordsDf)
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AgGrid(tRkeywordsDf, reload_data = False,
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update_mode="value_changed",
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columns_auto_size_mode = ColumnsAutoSizeMode.FIT_CONTENTS,
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height = 100 )
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st.markdown("###### Top few SDG Classified paragraph/text results ######")
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# c7, c8, c9 = st.columns([1, 10, 1])
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utils/sdg_classifier.py
CHANGED
@@ -97,6 +97,7 @@ def sdg_classification(haystackdoc:List[Document])->Tuple[DataFrame,Series]:
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x = x.rename_axis('SDG').reset_index()
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x["SDG"] = pd.to_numeric(x["SDG"])
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x['SDG_name'] = x['SDG'].apply(lambda x: _lab_dict[x])
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df= df.drop(['Relevancy'], axis = 1)
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x = x.rename_axis('SDG').reset_index()
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x["SDG"] = pd.to_numeric(x["SDG"])
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x['SDG_name'] = x['SDG'].apply(lambda x: _lab_dict[x])
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+
x['SDG'] = x['SDG'].apply(lambda x: "SDG "+str(x))
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df= df.drop(['Relevancy'], axis = 1)
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