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Python搞定表格可视化！
The following article is from pythonic生物人 Author pythonic生物人
来源丨经授权转自 code秘密花园（ID：code_mmhy）
作者丨ConardLi
分享一个Python工具plottable，轻松制作高度个性化的表格，底层为Matplotlib。
例如这样的，
# 导入相关包
from pathlib import Path
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from matplotlib.colors import LinearSegmentedColormap
from plottable import ColumnDefinition, Table
from plottable.cmap import normed_cmap
from plottable.formatters import decimal_to_percent
from plottable.plots import circled_image
plt.rcParams["font.family"] = ["DejaVu Sans"]
plt.rcParams["savefig.bbox"] = "tight"
# demo数据准备
cols = [
"team",
"points",
"group",
"spi",
"global_o",
"global_d",
"group_1",
"group_2",
"group_3",
"make_round_of_16",
"make_quarters",
"make_semis",
"make_final",
"win_league",
]
df = pd.read_csv(
"data/wwc_forecasts.csv",
usecols=cols,
)
colnames = [
"Team",
"Points",
"Group",
"SPI",
"OFF",
"DEF",
"1st Place",
"2nd Place",
"3rd Place",
"Make Rd Of 16",
"Make Quarters",
"Make Semis",
"Make Finals",
"Win World Cup",
]
col_to_name = dict(zip(cols, colnames))
flag_paths = list(Path("country_flags").glob("*.png"))
country_to_flagpath = {p.stem: p for p in flag_paths}
df[["spi", "global_o", "global_d"]] = df[["spi", "global_o",
"global_d"]].round(1)
df = df.rename(col_to_name, axis=1)
df = df.drop("Points", axis=1)
df.insert(0, "Flag", df["Team"].apply(lambda x: country_to_flagpath.get(x)))
df = df.set_index("Team")
# colormap准备
cmap = LinearSegmentedColormap.from_list(
name="bugw",
colors=["#ffffff", "#f2fbd2", "#c9ecb4", "#93d3ab", "#35b0ab"],
N=256)
team_rating_cols = ["SPI", "OFF", "DEF"]
group_stage_cols = ["1st Place", "2nd Place", "3rd Place"]
knockout_stage_cols = list(df.columns[-5:])
# table列个性化list，例如列名、列宽、字体、磅值等等
col_defs = ([
ColumnDefinition(
name="Flag",
title="Region",
textprops={"ha": "center"},
width=0.5,
plot_fn=circled_image,
),
ColumnDefinition(
name="Team",
textprops={
"ha": "left",
"weight": "bold"
},
width=1.5,
),
ColumnDefinition(
name="Group",
textprops={"ha": "center"},
width=0.75,
),
ColumnDefinition(
name="SPI",
group="Team Rating",
textprops={"ha": "center"},
width=0.75,
),
ColumnDefinition(
name="OFF",
width=0.75,
textprops={
"ha": "center",
"bbox": {
"boxstyle": "circle",
"pad": 0.35
},
},
cmap=normed_cmap(df["OFF"], cmap=matplotlib.cm.Blues, num_stds=2.5),
group="Team Rating",
),
ColumnDefinition(
name="DEF",
width=0.75,
textprops={
"ha": "center",
"bbox": {
"boxstyle": "circle",
"pad": 0.35
},
},
cmap=normed_cmap(df["DEF"], cmap=matplotlib.cm.Greens, num_stds=2.5),
group="Team Rating",
),
] + [
ColumnDefinition(
name=group_stage_cols[0],
title=group_stage_cols[0].replace(" ", "\n", 1),
formatter=decimal_to_percent,
group="Group Stage Chances",
border="left",
)
] + [
ColumnDefinition(
name=col,
title=col.replace(" ", "\n", 1),
formatter=decimal_to_percent,
group="Group Stage Chances",
) for col in group_stage_cols[1:]
] + [
ColumnDefinition(
name=knockout_stage_cols[0],
title=knockout_stage_cols[0].replace(" ", "\n", 1),
formatter=decimal_to_percent,
cmap=cmap,
group="Knockout Stage Chances",
border="left",
)
] + [
ColumnDefinition(
name=col,
title=col.replace(" ", "\n", 1),
formatter=decimal_to_percent,
cmap=cmap,
group="Knockout Stage Chances",
) for col in knockout_stage_cols[1:]
])
# plottable的Table方法制作表格
fig, ax = plt.subplots(figsize=(20, 22))
table = Table(
df,
column_definitions=col_defs,
row_dividers=True,
footer_divider=True,
ax=ax,
textprops={
"fontsize": 14
},
row_divider_kw={
"linewidth": 1,
"linestyle": (0, (1, 5))
},
col_label_divider_kw={
"linewidth": 1,
"linestyle": "-"
},
column_border_kw={
"linewidth": 1,
"linestyle": "-"
},
).autoset_fontcolors(colnames=["OFF", "DEF"])点分享
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