Spaces:
Running
Running
Update app.py
Browse files
app.py
CHANGED
@@ -212,11 +212,6 @@ if fetch_data:
|
|
212 |
items.append(item)
|
213 |
|
214 |
metadata_df = pd.DataFrame(items)
|
215 |
-
|
216 |
-
# Define custom completeness check
|
217 |
-
# Define completeness logic
|
218 |
-
def is_incomplete(value):
|
219 |
-
return pd.isna(value) or value in ["", "N/A", "null", None]
|
220 |
|
221 |
# New way to calculate incomplete record mask
|
222 |
incomplete_mask = metadata_df.apply(lambda row: row.map(is_incomplete), axis=1).any(axis=1)
|
@@ -234,9 +229,6 @@ if fetch_data:
|
|
234 |
stats_placeholder.markdown(stats_html, unsafe_allow_html=True)
|
235 |
|
236 |
|
237 |
-
|
238 |
-
st.sidebar.write(f"Incomplete Records: {len(metadata_df[metadata_df.isnull().any(axis=1)])}")
|
239 |
-
|
240 |
# Utility functions for deeper metadata quality analysis
|
241 |
def is_incomplete(value):
|
242 |
return pd.isna(value) or value in ["", "N/A", "null", None]
|
|
|
212 |
items.append(item)
|
213 |
|
214 |
metadata_df = pd.DataFrame(items)
|
|
|
|
|
|
|
|
|
|
|
215 |
|
216 |
# New way to calculate incomplete record mask
|
217 |
incomplete_mask = metadata_df.apply(lambda row: row.map(is_incomplete), axis=1).any(axis=1)
|
|
|
229 |
stats_placeholder.markdown(stats_html, unsafe_allow_html=True)
|
230 |
|
231 |
|
|
|
|
|
|
|
232 |
# Utility functions for deeper metadata quality analysis
|
233 |
def is_incomplete(value):
|
234 |
return pd.isna(value) or value in ["", "N/A", "null", None]
|