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@chalg
Last active April 2, 2024 02:49
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Leverage Great Tables (great_tables) python package to showcase month on month change percentage of Euro economic sentiment indicators.
from great_tables import GT, md, html, system_fonts
import pandas as pd
power_cie_prepared_tbl = pd.read_csv("./data/2023_cie_power_cons.csv")
# Create a Great Tables object
ciep_gt_tbl = GT(data=power_cie_prepared_tbl)
# Apply wider color ranges & formatting
gt_tbl = ciep_gt_tbl \
.fmt_percent(columns=['Hydro', 'Nuclear', 'Wind', 'Solar', 'Geothermal', 'Biomass', 'Gas',
'Coal', 'Oil', 'Unknown', 'Hydro Discharge', 'Battery Discharge'],
decimals=1) \
.fmt_number(columns=['CO2 Intensity'],
decimals=0) \
.data_color(
columns=['CO2 Intensity'],
palette=[
"#00A600", "#E6E600", "#E8C32E", "#D69C4E", "#Dc863B", "sienna", "sienna4", "tomato4", "brown"],
domain=[0, 900]
) \
.data_color(
columns=['Hydro', 'Nuclear', 'Wind', 'Solar','Geothermal'],
palette=["#00A600", "chartreuse3", "chartreuse4", "snow"][::-1],
domain=[0, 1]
) \
.data_color(
columns=['Hydro', 'Geothermal'],
palette=["#00A600", "chartreuse3", "chartreuse4", "snow"][::-1],
domain=[0, 1]
) \
.data_color(
columns=['Biomass'],
palette=["snow", "#EEC900", "#E8C32E", "#D69C4E"],
domain=[0, 0.3]
) \
.data_color(
columns=['Gas', 'Coal', 'Oil'],
palette=["tomato4", "sienna4", "#D69C4E", "#Dc863B", "snow"][::-1],
domain=[0, 1]
) \
.data_color(
columns=['Zone','Unknown', 'Hydro Discharge', 'Battery Discharge'],
palette=["snow", "snow", "snow", 'snow']
) \
.cols_width(
{'CO2 Intensity': '58px','Hydro': '58px', 'Nuclear': '58px', 'Wind': '58px', 'Solar': '58px',
'Geothermal': '58px', 'Biomass': '58px', 'Gas': '58px', 'Coal': '58px',
'Oil': '58px', 'Unknown': '58px', 'Hydro Discharge': '58px',
'Battery Discharge': '58px'}
) \
.tab_header(
title=md("2023 Mean **Carbon Intensity** (gCO2eq/kWh) and **Power Consumption** Breakdown (%)")
) \
.tab_source_note(
md(
'<br><div style="text-align: left;">'
"**Source**: api.electricitymap.org"
" | **Methodology**: https://www.electricitymaps.com/methodology."
" Some emissions factors are based on IPCC 2014 defaults, while some are based on more accurate regional factors."
" <br>All zones are publicly available on the *Carbon intensity and emission factors* tab via Google docs link."
" Rooftop solar not included in California ISO figures for California"
"</div>"
"<br>"
)
) \
.tab_options(
source_notes_font_size='x-small',
source_notes_padding=3,
table_font_names=system_fonts("humanist"),
data_row_padding='1px',
heading_background_color='antiquewhite',
source_notes_background_color='antiquewhite',
column_labels_background_color='antiquewhite',
table_background_color='snow',
data_row_padding_horizontal=3,
column_labels_padding_horizontal=58
) \
.cols_align(
align='center'
) \
.cols_align(
align='left',
columns=['Zone']
) \
.opt_table_outline()
gt_tbl
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