-
Notifications
You must be signed in to change notification settings - Fork 0
/
app.py
893 lines (823 loc) · 31.5 KB
/
app.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
################################ imporing libraries ################################
from re import X
import os
import dash
from plotly.subplots import make_subplots
import plotly.graph_objects as go
import dash_bootstrap_components as dbc
from dash import Input, Output, State, dcc, html
from dash_bootstrap_components._components.Navbar import Navbar
import plotly.express as px
import pandas as pd
from dash_bootstrap_templates import load_figure_template
import math
################################ importing Data ################################
################################################################################
Export_total = pd.read_csv("Data/Export_total.csv")
annual = pd.read_csv("Data/Annual_processed.csv", sep=",")
export_map = pd.read_csv('Data/for_map0.csv', sep=',')
import_map = pd.read_csv('Data/for_map1.csv', sep=',')
############################ Extracting Data ################################
############################################################################
##### les données de 5em graph #####
pays_exports = annual[
(annual['Libellé du flux'] == "Exportations FAB") | (annual['Libellé du flux'] == "Importations CAF")]
annualdf = pays_exports.set_index(['Libellé du pays', 'Libellé du flux'])
annualdf = annualdf.transpose().set_index(pd.date_range(start='2010-01-01', periods=11, freq='Y'))
annualdf = annualdf.unstack()
annualdf = annualdf.to_frame()[:]
annualdf = annualdf.reset_index()
##### for KpiS and others #####
total_import = annual[(annual["Libellé du flux"] == "Importations CAF")].groupby(["Libellé du flux"]).sum().sort_values(
"Valeur DHS 2020", ascending=False)
total_export = annual[(annual["Libellé du flux"] == "Exportations FAB")].groupby(["Libellé du flux"]).sum().sort_values(
"Valeur DHS 2020", ascending=False)
pays_export = annual[(annual["Libellé du flux"] == "Exportations FAB")].groupby(["Libellé du pays"]).sum().sort_values(
"Valeur DHS 2020", ascending=False)
pays_import = annual[(annual["Libellé du flux"] == "Importations CAF")].groupby(["Libellé du pays"]).sum().sort_values(
"Valeur DHS 2020", ascending=False)
pays_export0 = pays_export.transpose()
pays_export0["date"] = pd.date_range(start="2010-01-01", periods=11, freq="Y")
#### for Pie charts #######
continent_import = Export_total[(Export_total["Libellé du flux"] == "Importations CAF")].groupby(
["Continent"]).mean().sort_values("Total dh", ascending=False)
continent_export = Export_total[(Export_total["Libellé du flux"] == "Exportations FAB")].groupby(
["Continent"]).mean().sort_values("Total dh", ascending=False)
utilisation_import = Export_total[(Export_total["Libellé du flux"] == "Importations CAF")].groupby(
["Libellé du groupement d'utilisation"]).mean().sort_values("Total dh", ascending=False)
utilisation_export = Export_total[(Export_total["Libellé du flux"] == "Exportations FAB")].groupby(
["Libellé du groupement d'utilisation"]).mean().sort_values("Total dh", ascending=False)
##### for bar chart #######
section_export = Export_total[(Export_total["Libellé du flux"] == "Importations CAF")].groupby(
["Libellé de la section CTCI"]).mean().sort_values("Total dh", ascending=False)
section_import = Export_total[(Export_total["Libellé du flux"] == "Exportations FAB")].groupby(
["Libellé de la section CTCI"]).mean().sort_values("Total dh", ascending=False)
sections = df = pd.DataFrame()
sections['total imports'] = section_import['Total dh']
sections['total exports'] = section_export['Total dh']
################################ a function to deal with large numbers in the KPIs ################################
millnames = ["", " Mille", " Million", " Milliard", "000 milliards"]
def millify(n):
n = float(n)
millidx = max(
0,
min(
len(millnames) - 1, int(math.floor(0 if n == 0 else math.log10(abs(n)) / 3))
),
)
return "{:.0f}{}".format(n / 10 ** (3 * millidx), millnames[millidx])
########## some variables for KPIs
max_p_i = millify(pays_import["Valeur DHS 2020"][0])
max_p_i_i = pays_import.index[0]
max_p_e = millify(pays_export["Valeur DHS 2020"][0])
max_p_e_i = pays_export.index[0]
max_t_i = millify(total_import["Valeur DHS 2020"][0])
max_t_i_i = total_import.index[0]
max_t_e = millify(total_export["Valeur DHS 2020"][0])
max_t_e_i = total_export.index[0]
################################ Loading the theme and creating my personnalised palette ################################
load_figure_template(["QUARTZ"])
my_palette = ["#29d4f7", "#FF5677", "#40f190", "#B958A5", "#f7c76f", "cadetblue", "saddlebrown", "darkslateblue"]
############# initialisation de l'app dash #########
app = dash.Dash(__name__,
suppress_callback_exceptions=True,
external_stylesheets=[
dbc.themes.BOOTSTRAP,
dbc.icons.FONT_AWESOME,
"https://bootswatch.com/_vendor/bootstrap/dist/js/bootstrap.bundle.min.js",
"https://bootswatch.com/_vendor/bootstrap/dist/js/bootstrap.bundle.min.js",
],
# these meta_tags ensure content is scaled correctly on different devices
# see: https://www.w3schools.com/css/css_rwd_viewport.asp for more
meta_tags=[{"name": "viewport", "content": "width=device-width, initial-scale=1"}],
)
server = app.server
######### the functions used to draw the graphs #####
def drawFig():
labels = continent_import.index
# Create subplots: use 'domain' type for Pie subplot
fig = make_subplots(rows=1, cols=2, specs=[[{'type': 'domain'}, {'type': 'domain'}]])
fig.add_trace(
go.Pie(labels=labels, values=continent_import['Total dh'], name="Partition des importations par utilisation"),
1, 1)
fig.add_trace(
go.Pie(labels=labels, values=continent_export['Total dh'], name="Partition des exportations par utilisation"),
1, 2)
fig.update_traces(hole=.5, hoverinfo="label+percent+name")
fig.update_layout(
annotations=[dict(text='Import', x=0.20, y=0.5, font_size=14, showarrow=False),
dict(text='Export', x=0.80, y=0.5, font_size=14, showarrow=False)])
fig.update_layout(margin=dict(t=0, b=0, l=0, r=0))
fig.update_layout(
{
"plot_bgcolor": "rgba(138, 138, 138, 0)",
"paper_bgcolor": "rgba(138, 138, 138, 0)",
},
font=dict(family="Lato, monospace", size=12, color="#fff"),
xaxis={'showgrid': False},
yaxis={'showgrid': True}
)
fig.update_layout(legend_font_size=9)
fig.update_layout(legend_itemsizing='trace')
fig.update_layout(legend_uirevision=X)
fig.update_traces(textposition='inside')
fig.update_layout(uniformtext_minsize=12, uniformtext_mode='hide')
return html.Div(
[
html.Div(
[
html.Div("Partition des importations par continents(moyen des 3 derniers années)"),
html.Br(),
dcc.Graph(
id="example-graph",
figure=fig,
responsive=True,
style={"width": "auto", "height": "270px"},
),
],
style={"textAlign": "center"},
className="mycard",
)
]
)
def drawMap():
return html.Div(
[
html.Div(
[
dbc.Tabs([
dbc.Tab(label="Exportations", tab_id="tab-1", tabClassName="flex-grow-1 text-center",
active_label_style={'background-color': 'rgb(196, 125, 230)',
'color': 'rgb(42, 42, 53)'}, tab_style={'margin': '0px'},
label_style={'background-color': '#e9e9e92a', 'color': 'rgb(42, 42, 53)'}),
dbc.Tab(label="Importations", tab_id="tab-2", tabClassName="flex-grow-1 text-center",
active_label_style={'background-color': 'rgb(196, 125, 230)',
'color': 'rgb(42, 42, 53)'}, tab_style={'margin': '0px'},
label_style={'background-color': '#e9e9e92a', 'color': 'rgb(42, 42, 53)'}),
],
id="tabs",
active_tab="tab-1", style={'padding': '0px 40px', }
),
html.Div(id="content"),
],
style={"textAlign": "center"},
className="mycard",
)
]
)
def drawFigure3():
fig = px.pie(utilisation_import,
values='Total dh',
names=utilisation_import.index,
color_discrete_sequence=my_palette,
)
fig.update_layout(
{
"plot_bgcolor": "rgba(0, 0, 0, 0)",
"paper_bgcolor": "rgba(0, 0, 0, 0)",
},
font=dict(family="Lato, monospace", size=12, color="#fff"),
)
fig.update_layout(legend_font_size=9)
fig.update_layout(legend_itemsizing='trace')
fig.update_layout(legend_uirevision=X)
fig.update_traces(textposition='inside')
fig.update_layout(uniformtext_minsize=12, uniformtext_mode='hide')
return html.Div(
[
html.Div(
[
html.Div("Partition des importations par utilisation(moyen des 3 derniers années)"),
dcc.Graph(
id="3-graph",
figure=fig,
responsive=True,
style={"width": "auto", "height": "270px"},
),
],
style={"textAlign": "center"},
className="mycard",
)
]
)
def drawFigure4():
fig = px.pie(utilisation_export,
values='Total dh',
names=utilisation_export.index,
color_discrete_sequence=my_palette,
)
fig.update_layout(
{
"plot_bgcolor": "rgba(0, 0, 0, 0)",
"paper_bgcolor": "rgba(0, 0, 0, 0)",
},
font=dict(family="Lato, monospace", size=12, color="#fff"),
)
fig.update_layout(legend_font_size=9)
fig.update_layout(legend_itemsizing='trace')
fig.update_layout(legend_uirevision=X)
fig.update_traces(textposition='inside')
fig.update_layout(uniformtext_minsize=12, uniformtext_mode='hide')
return html.Div(
[
html.Div(
[
html.Div("Partition des exportations par utilisation(moyen des 3 derniers années)"),
dcc.Graph(
id="4-graph",
figure=fig,
responsive=True,
style={"width": "auto", "height": "270px"},
),
],
style={"textAlign": "center"},
className="mycard",
)
]
)
def drawSections(col):
fig = px.bar(
sections.sort_values(by=col, ascending=False),
x=sections.index,
y=col,
orientation='v',
color_discrete_sequence=my_palette,
)
fig.update_layout(
{
"plot_bgcolor": "rgba(138, 138, 138, 0)",
"paper_bgcolor": "rgba(138, 138, 138, 0)",
},
font=dict(family="Lato, monospace", size=12, color="#fff"),
xaxis={
'showgrid': False
},
yaxis={
'showgrid': True
}
)
fig.update_layout(
margin=dict(b=0))
fig.update_traces(textfont_size=8, textangle=0, textposition="outside", cliponaxis=False)
fig.update_traces(texttemplate='%{text:.2s}', textposition='outside')
fig.update_layout(uniformtext_minsize=10, uniformtext_mode='hide')
fig.update_layout(barmode='stack', xaxis={'categoryorder': 'category ascending'})
fig.update_layout(xaxis={'visible': False, 'showticklabels': False})
return html.Div(
[
html.Div(
[
html.Div("Partitions des " + col[6:] + " par section"),
dcc.Graph(
id="example-graph",
figure=fig,
responsive=True,
style={"width": "auto", "height": "270px"},
),
],
style={"textAlign": "center"},
className="mycard",
)
]
)
def myf(Title, theid):
return html.Div(
[
html.Div(
[
dbc.Row([
dbc.Col(dcc.Dropdown(
id="ticker",
options=[
{"label": x, "value": x}
for x in pays_export0.columns[0:]
], style=
{'width': '165px',
'color': '#212121',
'background-color': '#83838350',
'align': 'center',
'font-size': '13px'
},
value=pays_export0.columns[0],
clearable=True, searchable=False,
), md=6, sm=6, lg=6, xl=6),
dbc.Col(html.Div(Title), md=6, sm=6, lg=6, xl=6)
]),
dcc.Graph(
id=theid,
responsive=True,
style={"width": "auto", "height": "270px"},
),
],
style={"textAlign": "center"},
className="mycard",
)
]
)
######## function to return the KPIs cards ######
def kpi1():
return html.Div(
[
html.Div(
[
html.Div("Plus grand importateur ", className="title"),
html.Hr(),
html.B(
max_p_i + " Dh"),
html.Br(),
max_p_i_i,
],
style={"textAlign": "center"},
className="KPI",
)
]
)
def kpi2():
return html.Div(
[
html.Div(
[
html.Div("Plus grand exportateur ", className="title"),
html.Hr(),
html.B(max_p_e + " Dh"),
html.Br(),
max_p_e_i,
],
style={"textAlign": "center"},
className="KPI",
)
]
)
def kpi3():
return html.Div(
[
html.Div(
[
html.Div("Total exportations 2020", className="title"),
html.Hr(),
html.B(max_t_e + " Dh"),
html.Br(),
max_t_e_i,
],
style={"textAlign": "center"},
className="KPI",
)
]
)
def kpi4():
return html.Div(
[
html.Div(
[
html.Div("Total importations 2020", className="title"),
html.Hr(),
html.B(max_t_i + " Dh"),
html.Br(),
max_t_i_i,
],
style={"textAlign": "center"},
className="KPI",
)
]
)
########## The header of sidebare ##########
sidebar_header = dbc.Row(
[
dbc.Col(
html.H6("OEM", className="display-6 "),
align="start",
xs=8,
md=8,
lg=8,
xl=8,
xxl=8,
sm=8,
),
dbc.Col(" ", xs=2, md=2, lg=2, xl=2, xxl=2, sm=2),
dbc.Col(
[
html.Button(
# use the Bootstrap navbar-toggler classes to style
html.Span(className="fa fa-bars"),
className="navbar-toggler",
# the navbar-toggler classes don't set color
style={
"color": "rgba(255, 255, 255, 0.9)",
"border": "none",
},
id="navbar-toggle",
),
html.Button(
# use the Bootstrap navbar-toggler classes to style
html.Span(className="fa fa-bars"),
className="navbar-toggler",
# the navbar-toggler classes don't set color
style={
"color": "rgba(255, 255, 255, 0.9)",
"border": "none",
},
id="sidebar-toggle",
),
],
# the column containing the toggle will be only as wide as the
# toggle, resulting in the toggle being right aligned
className="mb-3",
# vertically align the toggle in the center
align="end",
xs=2,
md=2,
lg=2,
xl=2,
xxl=2,
sm=2,
),
]
)
########### the sidebar #############
sidebar = html.Div(
[
sidebar_header,
html.Div(
[
html.Hr(),
html.P(
"Ce tableau de bord s'inscrit dans le cadre d'un projet académique de data visualisation",
className="lead",
),
],
id="blurb",
),
# use the Collapse component to animate hiding / revealing links
dbc.Collapse(
dbc.Nav(
[
dbc.NavLink("Home", href="/", active="exact"),
dbc.NavLink("Data prep", href="/page-1", active="exact"),
dbc.NavLink("About", href="/page-2", active="exact"),
],
vertical=True,
pills=True,
),
id="collapse",
),
],
id="sidebar",
)
######### items to define the theme and change it #####
content = html.Div(id="page-content")
blank = html.Div(id="blank_output")
############ the home page (dashboard) ###########
row = html.Div(
[
dbc.Row(
[
dbc.Col("", xs=2, sm=2, md=2, lg=2, xl=2),
dbc.Col(html.H6(""), xs=2, sm=2, md=2, lg=2, xl=2),
dbc.Col("", xs=2, sm=2, md=2, lg=2, xl=2),
dbc.Col("", xs=2, sm=2, md=2, lg=2, xl=2),
dbc.Col(
html.Div(
[
html.Span(
className="fa fa-sun mt-1",
),
html.Span(
[
dbc.Switch(
value=True,
id="theme",
className="ms-4 switcher_icon",
),
]
),
html.Span(className="fa fa-moon mt-1"),
],
className="justify-content-center switcher",
),
xs=4,
sm=4,
md=4,
lg=4,
xl=4,
),
]
),
html.Br(),
html.Div(
[
dbc.Row(
[
dbc.Row(
dbc.Col(html.B("Quelques metrics de 2020")),
style={"textAlign": "center"},
className="titre",
),
dbc.Col(
[kpi1()],
xs=6,
sm=6,
md=6,
lg=3,
xl=2,
),
dbc.Col(
[kpi2()],
xs=6,
sm=6,
md=6,
lg=3,
xl=2,
),
dbc.Col(
[kpi3()],
xs=6,
sm=6,
md=6,
lg=3,
xl=2,
),
dbc.Col(
[kpi4()],
xs=6,
sm=6,
md=6,
lg=3,
xl=2,
),
],
id="",
style={"textAlign": "center"},
align="center",
className="justify-content-between",
),
html.Hr(),
dbc.Row(
[
dbc.Col([drawFig()], xs=12, sm=12, md=6, lg=6, xl=6),
dbc.Col([myf('Les échanges entre 2010 et 2020 ', "time-series-chart")
], xs=12, sm=12, md=12, lg=6, xl=6, ),
dbc.Col([drawFigure3()], xs=12, sm=12, md=6, lg=6, xl=6),
dbc.Col([drawFigure4()], xs=12, sm=12, md=6, lg=6, xl=6),
dbc.Col([drawMap()], xs=12, sm=12, md=12, lg=12, xl=12),
dbc.Col([drawSections("total exports")], xs=12, sm=12, md=12, lg=6, xl=6),
dbc.Col([drawSections("total imports")], xs=12, sm=12, md=12, lg=6, xl=6),
],
id="",
style={"textAlign": "center"},
align="center",
className="justify-content-center",
),
],
style={"textAlign": "center"},
className="justify-content-center bCard",
),
],
)
########################################################################################
#################################### callbacks #########################################
############ assigning content to pages depending on a url ############
app.layout = html.Div([dcc.Location(id="url"), sidebar, blank, content])
############ swwitching between themes ############
app.clientside_callback(
"""
function(themeToggle) {
// To use different themes, change these links:
const theme1 = "https://bootswatch.com/5/CYBORG/bootstrap.min.css"
const theme2 = "https://bootswatch.com/5/quartz/bootstrap.min.css"
const stylesheet = document.querySelector('link[rel=stylesheet][href^="https://bootswatch"]')
var themeLink = themeToggle ? theme1 : theme2;
stylesheet.href = themeLink
}
""",
Output("blank_output", "children"),
Input("theme", "value"),
)
############ render page according to path ############
@app.callback(Output("page-content", "children"), [Input("url", "pathname")])
def render_page_content(pathname):
if pathname == "/":
return html.Div(row)
elif pathname == "/page-1":
return html.Div(
[
html.Div(
[
html.H2("HEY THERE !", style={"textAlign": "center"}),
html.Hr(),
html.H6(
"Cette dashbord traite les échanges d'importation et exportation entre le maroc et les autres pays",
),
html.Div(
"les données utilisées dans cette app sont passé d'abord par des étapes de traitement , exploration... ",
),
html.P("le notebook suivant montre ces étapes :"),
html.Iframe(
src="assets/Data_prep.html", width="100%", height="560px"
),
],
className="mycard",
)
]
)
elif pathname == "/page-2":
return html.Div(
[
html.Br(),
html.Br(),
html.Div(
[
html.Br(),
html.Br(),
html.H4("Aout this App", style={"textAlign": "center"}),
html.Hr(),
html.Div(
"Les données utilisées sont extraites du site officiel de l'office des changes marocain"
),
html.A(
"lien vers le websit officiel de l'office",
href="https://www.oc.gov.ma/",
className="link",
),
html.Br(),
html.Br(),
html.Br(),
html.Br(),
html.A(
html.Span(
className="fab fa-linkedin fa-2x",
),
href="https://www.linkedin.com/in/hamid-abdellaoui/",
),
html.A(
html.Span(
className="fab fa-github-square fa-2x ms-2",
),
href="https://github.com/Hamid-abdellaoui",
),
html.A(
html.Span(
className="fa fa-envelope-square fa-2x ms-2",
),
href="mailto:hamidabdellaoui55@gmail.com",
),
],
className="mycard",
),
],
)
# If the user tries to reach a different page, return a 404 message
else:
return dbc.Row(
[
html.H1("404: Not found", className="text-danger"),
html.Hr(),
html.P(f"The pathname {pathname} was not recognised..."),
]
)
############ sidebar toggletr ############
@app.callback(
Output("sidebar", "className"),
[Input("sidebar-toggle", "n_clicks")],
[State("sidebar", "className")],
)
def toggle_classname(n, classname):
if n and classname == "":
return "collapsed"
return ""
############ navbar toggletr ############
@app.callback(
Output("collapse", "is_open"),
[Input("navbar-toggle", "n_clicks")],
[State("collapse", "is_open")],
)
def toggle_collapse(n, is_open):
if n:
return not is_open
return is_open
############ emprtations/exportations by country line chart ############
@app.callback(Output("time-series-chart", "figure"), [Input("ticker", "value")])
def display_time_series(ticker):
fig = px.line(annualdf[(annualdf['Libellé du pays'] == ticker)], x='level_2', y=0, color='Libellé du flux',
labels={
"level_2": "Date",
"0": "valeur en DH"
}, color_discrete_sequence=my_palette,
)
fig.update_layout(
{
"plot_bgcolor": "rgba(0, 0, 0, 0)",
"paper_bgcolor": "rgba(0, 0, 0, 0)",
},
font=dict(family="Lato, monospace", size=12, color="#fff"),
xaxis={
'showgrid': False
},
yaxis={
'showgrid': True
}
)
fig.update_xaxes(showline=True, linewidth=1, linecolor='rgba(9, 145, 199, 0.932)',
gridcolor='rgba(240, 240, 240, 0.233) ')
fig.update_yaxes(showline=True, linewidth=1, linecolor='rgba(9, 145, 199, 0.932)',
gridcolor='rgba(240, 240, 240, 0.233) ')
return fig
############ the map graph (Choropleth) ############
@app.callback(Output("content", "children"), [Input("tabs", "active_tab")])
def switch_tab(at):
if at == "tab-1":
fig = go.Figure(data=go.Choropleth(
locations=export_map['alpha-3'],
z=export_map['Valeur moyen des exportations sur 10ans'],
text=export_map['Libellé du pays'],
colorscale=['#99004d', '#ff3287', '#fc76c4', '#ca89bd'],
# colorscale='Blues',
autocolorscale=False,
reversescale=True,
marker_line_color='white',
marker_line_width=1,
colorbar_tickprefix='dh ',
colorbar_title='Exports en Dh', ))
fig.update_layout(
geo=dict(
showframe=False,
showcoastlines=False,
projection_type='equirectangular'),
annotations=[dict(
x=0.5,
y=0,
xref='paper',
yref='paper',
text='Moyenne annuel entre 2010 et 2020',
showarrow=False)
]
)
fig.update_layout(
margin=dict(l=0, r=0, t=0, b=0),
paper_bgcolor="rgba(224, 223, 223, 0.137)")
fig.update_layout(geo=dict(bgcolor='rgba(0,0,0,0)'))
fig.update_layout(hovermode='closest', )
fig.update_layout(
{
"plot_bgcolor": "rgba(0, 0, 0, 0)",
"paper_bgcolor": "rgba(0, 0, 0, 0)",
},
font=dict(family="Lato, monospace", size=12, color="#fff"),
)
fig.update_coloraxes(colorbar_exponentformat="power")
return dcc.Graph(
figure=fig,
responsive=True,
style={"width": "auto", "height": "420px"},
),
elif at == "tab-2":
fig = go.Figure(data=go.Choropleth(
locations=import_map['alpha-3'],
z=import_map['Valeur moyen des importations sur 10ans'],
text=import_map['Libellé du pays'],
colorscale=['#99004d', '#ff3287', '#fc76c4', '#ca89bd'],
# colorscale='Blues',
autocolorscale=False,
reversescale=True,
marker_line_color='white',
marker_line_width=1,
colorbar_tickprefix='dh ',
colorbar_title='Imports en Dh', ))
fig.update_layout(
geo=dict(
showframe=False,
showcoastlines=False,
projection_type='equirectangular'),
annotations=[dict(
x=0.5,
y=0,
xref='paper',
yref='paper',
text='Moyenne annuel entre 2010 et 2020',
showarrow=False)
]
)
fig.update_layout(
margin=dict(l=0, r=0, t=0, b=0),
paper_bgcolor="rgba(224, 223, 223, 0.137)")
fig.update_layout(geo=dict(bgcolor='rgba(0,0,0,0)'))
fig.update_layout(hovermode='closest', )
fig.update_layout(
{
"plot_bgcolor": "rgba(0, 0, 0, 0)",
"paper_bgcolor": "rgba(0, 0, 0, 0)",
},
font=dict(family="Lato, monospace", size=12, color="#fff"),
)
fig.update_coloraxes(colorbar_exponentformat="power")
return dcc.Graph(
figure=fig,
responsive=True,
style={"width": "auto", "height": "420px"},
),
############ starting the server ########
if __name__ == "__main__":
app.run_server(
# port=8080,
# debug=False,
# host="0.0.0.0",
)