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gva_sectors.py
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gva_sectors.py
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import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
from collections import OrderedDict
import dash_table
from utils import get_excel
import pandas as pd
from app import app
filename = get_excel("gva_sectors", "data/2018/economic-aggregates/S1.6.xlsx")
data = pd.read_excel(filename)
years = data.iloc[5:6, 2:-2]
year_set = list(OrderedDict.fromkeys(years.values[0]).keys())
process = data[7:]
sections = process.iloc[:, 0]
main_sections = [index for index in sections.index if sections[index].isdigit()]
rows = [data.iloc[idx] for idx in main_sections]
labels = [row.iloc[-1] for row in rows[0:-1]]
labelIds = [row.iloc[-2] for row in rows[0:-1]]
def app_layout():
children = [dcc.Tab(label=year, value=year) for year in year_set]
categories = labels.copy()
categories.insert(0, "Main Sections")
label_ids = labelIds.copy()
label_ids.insert(0, "0")
return (
html.H2("Gross Value Added Sectors"),
html.Div(
[
dcc.Dropdown(
id="category",
options=[
{"label": category, "value": label_ids[idx]}
for (idx, category) in enumerate(categories)
],
placeholder="Select a category",
value="0",
)
],
style={
"width": "30%",
"display": "block",
"align": "right",
"margin-left": "auto",
"margin-right": "0",
"margin-bottom": "20px",
},
),
html.Div(
[
dcc.Tabs(id="tabs", value=year_set[-1], children=children),
html.Div(id="output-tab"),
generate_table(data),
],
className="container",
),
)
def generate_table(_dataframe, _max_rows=10):
data = pd.read_excel(filename, header=None)
df = data[6:]
df.columns = df.iloc[0].fillna(value=pd.Series(range(100)))
return dash_table.DataTable(
data=df.to_dict("rows"),
columns=[{"id": c, "name": c} for c in df.columns],
style_table={
"height": "400px",
"overflowY": "scroll",
"border": "thin lightgrey solid",
},
)
layout = app_layout()
def filter(year, _category, rows, labels, remove=False):
cu_index, co_index = [
index for index in years.transpose().index if years[index].iloc[0] == year
]
filtered = rows[0:-1] if remove else rows
cu_values = [row[cu_index] for row in filtered]
co_values = [row[co_index] for row in filtered]
data_cu = [
{"values": cu_values, "type": "pie", "labels": labels},
]
data_co = [
{"values": co_values, "type": "pie", "labels": labels},
]
return html.Div(
[
html.H2("Current Price"),
dcc.Graph(
id="cp-graph",
figure={
"data": data_cu,
"layout": {
"margin": {"l": 30, "r": 0, "b": 30, "t": 0},
"name": "Current Price",
},
},
),
html.H2("Constant Price"),
dcc.Graph(
id="co-graph",
figure={
"data": data_co,
"layout": {
"margin": {"l": 30, "r": 0, "b": 30, "t": 0},
"name": "Cost Price",
},
},
),
]
)
@app.callback(
Output("output-tab", "children"),
[Input("tabs", "value"), Input("category", "value")],
)
def display_content(year, category):
if category and category != "0":
current_index = float(category)
filtered = [
data.iloc[index]
for index in sections.index
if float(sections[index]) > current_index
and float(sections[index]) < current_index + 1
]
if len(filtered) == 0:
filtered = [
data.iloc[index]
for index in sections.index
if float(sections[index]) == current_index
]
sublabels = [row.iloc[-1] for row in filtered]
return filter(year, category, filtered, sublabels)
return filter(year, category, rows, labels, remove=True)