Py.Cafe
Global Labor Market Insights 2025
- folderfigures/
- app.py
- requirements.txt
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
from dash import Dash, Input, Output, dcc, html
import dash_bootstrap_components as dbc
import dash_customizable_app_style as dcas
import plotly.express as px
from plotly.graph_objects import Figure
import pandas as pd
from figures import plots
gender_parity_df: pd.DataFrame = pd.read_csv("https://raw.githubusercontent.com/plotly/Figure-Friday/refs/heads/main/2025/week-26/gender-parity-in-managerial-positions.csv")
gender_pay_gap_df: pd.DataFrame = pd.read_csv("https://raw.githubusercontent.com/plotly/Figure-Friday/refs/heads/main/2025/week-26/gender-pay-gap.csv")
labor_product_df: pd.DataFrame = pd.read_csv("https://raw.githubusercontent.com/plotly/Figure-Friday/refs/heads/main/2025/week-26/labor-productivity.csv")
unemployment_df: pd.DataFrame = pd.read_csv("https://raw.githubusercontent.com/plotly/Figure-Friday/refs/heads/main/2025/week-26/unemployment.csv")
parity_grid = plots.create_grid(gender_parity_df, 'parity_grid')
pay_gap_grid = plots.create_grid(gender_pay_gap_df, 'pay_gap_grid')
bor_par_grid = plots.create_grid(labor_product_df, 'bor_par_grid')
unemployment_grid = plots.create_grid(unemployment_df, 'unemployment_grid')
app = Dash ("Figure Friday 2025 week 26", external_stylesheets=[dbc.themes.BOOTSTRAP])
# App layout
app.layout = html.Div(
id = "main_container",
style = {"minHeight": "100vh"},
children = [
dcas.customize_app_selectors(),
html.Div(
id = "main_div",
className = "m-0 p-2 w-100",
children = [
html.Div(
className = "row m-0 p-0",
children = [
html.H1("State of the global labor market", className="p-4 pb-3 fw-bold text-primary mb-0 border-bottom"),
dbc.Row([
dbc.Col(
html.P("Select dataset",
className = 'ms-3 mt-4 fs-5'),
width = 'auto'),
dbc.Col(
dcc.Dropdown(
id = 'dataset',
className = 'text-dark mt-4',
options = ['Gender parity', 'Genter pay gap', 'Labor productivity', 'Unemployment'],
value = 'Labor productivity'),
width = 4),
]),
dbc.Row(id = "dataset_title",
className='text-center fs-4 mt-4'),
# Line
html.Div(
className = "col-6 m-0 p-0",
children = [
dcc.Loading(
children = [
dcc.Store(id={"type": "figure-store", "index": "line"}),
dcc.Graph(id={"type": "graph", "index": "line"}),
]),
]),
# Heatmap
html.Div(
className = "col-6 m-0 p-0",
children = [
dcc.Loading(
children = [
dcc.Store(id={"type": "figure-store", "index": "heatmap"}),
dcc.Graph(id={"type": "graph", "index": "heatmap"}),
])
]),
# Box
html.Div(
className = "col-4 m-0 p-0",
children = [
dcc.Loading(
children = [
dcc.Store(id={"type": "figure-store", "index": "box"}),
dcc.Graph(id={"type": "graph", "index": "box"}),
])
]),
# Bar
html.Div(
className = "col-8 m-0 p-0",
children = [
dcc.Loading(
children = [
dcc.Store(id={"type": "figure-store", "index": "bar"}),
dcc.Graph(id={"type": "graph", "index": "bar"}),
])
]),
# Grid
html.Div(
id = 'dataset_grid',
className ='row m-0 p-0'),
]
),
])
])
@app.callback(
Output({"type": "figure-store", "index": "line"}, 'data'),
Output({"type": "figure-store", "index": "heatmap"}, 'data'),
Output({"type": "figure-store", "index": "box"}, 'data'),
Output({"type": "figure-store", "index": "bar"}, 'data'),
Output('dataset_grid', 'children'),
Output('dataset_title', 'children'),
Input('dataset', 'value')
)
def update_plot(dataset):
if dataset == 'Gender parity':
df = gender_parity_df
dataset_grid = parity_grid
elif dataset == 'Genter pay gap':
df = gender_pay_gap_df
dataset_grid = pay_gap_grid
elif dataset == 'Labor productivity':
df = labor_product_df
dataset_grid = bor_par_grid
else:
df = unemployment_df
dataset_grid = unemployment_grid
dataset_title = html.P(f"{dataset} changes over time")
#Line
fig = px.line(df, x='Year', y=df.columns[1:].tolist())
fig.update_layout(legend_title_text='World Area')
fig.update_xaxes( showline = True,
showgrid = False,
linewidth = 0.5,
linecolor = 'gray',
mirror = False,
zeroline = True)
fig.update_yaxes( showline = True,
showgrid = False,
linewidth = 0.5,
linecolor = 'gray',
mirror = False,
zeroline = True)
columns_to_use = df.columns[1:].tolist()
df_melted = df.melt(id_vars = 'Year',
value_vars = columns_to_use,
var_name = 'World Area',
value_name = 'Value')
years_sorted = sorted(df_melted['Year'].unique())
# Heatmap
heatmap = px.density_heatmap(df_melted,
x='Year',
y='World Area',
z='Value',
color_continuous_scale='Viridis',
nbinsx=len(years_sorted),
category_orders={'Year': years_sorted},
histfunc='avg')
heatmap.update_layout(coloraxis_colorbar=dict(title="% Average"))
heatmap.update_xaxes(type='category', tickangle=45)
# Box
box = px.box(df_melted, x='World Area', y='Value', color='World Area')
box.update_xaxes(type='category', tickangle=45)
box.update_xaxes( showline = True,
showgrid = False,
linewidth = 0.5,
linecolor = 'gray',
mirror = False,
zeroline = True)
box.update_yaxes( showline = True,
showgrid = False,
linewidth = 0.5,
linecolor = 'gray',
mirror = False,
zeroline = True)
# Bar
bar = px.bar(df_melted, x='Year', y='Value', color='World Area', barmode='stack')
bar.update_xaxes(type='category', tickangle=45)
bar.update_xaxes( showline = True,
showgrid = False,
linewidth = 0.5,
linecolor = 'gray',
mirror = False,
zeroline = True)
bar.update_yaxes( showline = True,
showgrid = False,
linewidth = 0.5,
linecolor = 'gray',
mirror = False,
zeroline = True)
return fig.to_dict(), heatmap.to_dict(), box.to_dict(), bar.to_dict(), dataset_grid, dataset_title
if __name__ == "__main__":
app.run(debug=False)