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recopytex
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lafrite:refact
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4 Commits
e8bf0b3f0a ... 412e624791

Author SHA1 Message Date
Bertrand Benjamin 412e624791 Merge remote-tracking branch 'origin/dev' into dev 2021-01-21 09:57:33 +01:00
Bertrand Benjamin e15119605f Merge branch 'dev' of git_opytex:/lafrite/recopytex into dev 2021-01-21 09:38:58 +01:00
Bertrand Benjamin 494567cdb5 Merge branch 'dev' of git_opytex:/lafrite/recopytex into dev 2021-01-21 09:25:58 +01:00
Bertrand Benjamin a14d47b15c Feat: Clean empty fig 2021-01-15 17:49:30 +01:00
1 changed files with 36 additions and 49 deletions
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85
recopytex/dashboard/exam_analysis/app.py
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@ -75,53 +75,40 @@ layout = html.Div(
),
html.Div(
[
html.Div(
dash_table.DataTable(
id="final_score_table",
columns=[
{"id": "Eleve", "name": "Élève"},
{"id": "Note", "name": "Note"},
{"id": "Bareme", "name": "Barème"},
],
data=[],
style_data_conditional=[
{
"if": {"row_index": "odd"},
"backgroundColor": "rgb(248, 248, 248)",
}
],
style_data={
"width": "100px",
"maxWidth": "100px",
"minWidth": "100px",
},
),
id="final_score_table_container",
),
html.Div(
[
dash_table.DataTable(
id="final_score_describe",
columns=[
{"id": "count", "name": "count"},
{"id": "mean", "name": "mean"},
{"id": "std", "name": "std"},
{"id": "min", "name": "min"},
{"id": "25%", "name": "25%"},
{"id": "50%", "name": "50%"},
{"id": "75%", "name": "75%"},
{"id": "max", "name": "max"},
],
),
dcc.Graph(
id="fig_assessment_hist",
),
dcc.Graph(id="fig_competences"),
],
id="desc_plots",
),
],
id="analysis",
"Evaluation: ",
dbc.Select(id="csv"),
]
),
],
),
html.H2("Résultats"),
dbc.Row(
[
dbc.Col(
dash_table.DataTable(
id="final_score_table",
columns=[
{"id": "Eleve", "name": "Élève"},
{"id": "Note", "name": "Note"},
{"id": "Bareme", "name": "Barème"},
],
data=[],
style_data_conditional=[
{
"if": {"row_index": "odd"},
"backgroundColor": "rgb(248, 248, 248)",
}
],
style_header={
"backgroundColor": "rgb(230, 230, 230)",
"fontWeight": "bold",
},
style_data={
"width": "100px",
"maxWidth": "100px",
"minWidth": "100px",
},
)
),
html.Div(
[
@ -231,7 +218,7 @@ def update_final_scores_hist(data):
assessment_scores = pd.DataFrame.from_records(data)
if assessment_scores.empty:
return [{}]
return [{'data': [], 'layout':[]}]
ranges = np.linspace(
-0.5,
@ -278,7 +265,7 @@ def update_competence_fig(data):
scores = flat_df_students(scores).dropna(subset=["Score"])
if scores.empty:
return [{}]
return [{'data': [], 'layout':[]}]
scores = pp_q_scores(scores)
pt = pd.pivot_table(