Python groupby 和 count 显示在图上

Question

请帮助正确书写。在图片上，我有一个 table，其中包含“团队”和“积分”。我想计算每个 F1 Team 收集了多少分以显示在情节上。我试着这样做：

team_points= cons.groupby('Team')['Points'].count()
team_points = pd.DataFrame(team_points)
team_points.columns = ['Points']
team_points.reset_index(level=0, inplace=True)

team_points.sort_values(by=['Points'], inplace=True, 
ascending=False)
team_points = team_points.head(10)
team_points = team_points[::-1]

fig = px.bar(team_points, x='Team', 
y='Points',color='Points',width=750, height=500)
fig.update_layout(title={'text': 'Teams with The Most Championships 
Won','y':0.95,'x':0.5})
fig.show()

Table

Answer 1

你的pandas代码做的事情很奇怪

确保 points 是数字
groupby().agg() 得到总数
已筛选出超过 100 分的团队以限制条数
plotly 代码那么简单

import plotly.express as px
import requests
import pandas as pd

res = requests.get("http://ergast.com/api/f1/constructorStandings.json", params={"limit":1000})
df = (pd.DataFrame(res.json()["MRData"]["StandingsTable"]["StandingsLists"])
 .explode("ConstructorStandings").reset_index(drop=True)
 .pipe(lambda d: d.loc[:,["season","round"]].join(d["ConstructorStandings"].apply(pd.Series)))
 .pipe(lambda d: d.join(d["Constructor"].apply(pd.Series))).drop(columns="Constructor")
)
df["points"] = pd.to_numeric(df["points"])

dfp = df.groupby(["name"]).agg({"points":"sum"}).loc[lambda d: d["points"].gt(100)]

px.bar(dfp, x=dfp.index, y="points", color="points")

Python groupby 和 count 显示在图上

Python groupby and count to show on the plot

python

pandas

plotly-python