我假裝使用以下數據框的過濾器制作散點圖（代表整個賽季的球員、球隊和賽季，并計算籃球隊球員所做的輔助和非輔助點）：player team_name season assisted notassistedA. DANRIDGE NACIONAL Season_17_18 130 445A. DANRIDGE NACIONAL Season_18_19 132 382D. ROBINSON TROUVILLE Season_18_19 89 286D. DAVIS AGUADA Season_18_19 101 281E. BATISTA WELCOME Season_17_18 148 278F. MARTINEZ GOES Season_18_19 52 259D. ALVAREZ AGUADA Season_17_18 114 246M. HICKS H. MACABI Season_17_18 140 245在 x 軸上我想放置輔助點，在 y 軸上放置非輔助點。但我也想按賽季、球隊和球員進行過濾，所以當我選擇球隊的一名確定球員時，我可以看到他們的分數用一種顏色顯示，而其他分數顯示為灰色，或者例如，如果我想選擇兩個或更多我可以在他們之間進行比較（用不同的顏色），并且其他點是可見的，但是是灰色的。我還想比較兩個不同球隊的球員和過濾器的組合。我正在學習數據科學，使用圖書館 plotly express 我可以制作散點圖并按團隊過濾，我可以比較兩個不同的團隊（或賽季或球員）。但是我無法以一種奇特的方式添加多個過濾器，而且我也不知道如何顯示選定的過濾器并將其他過濾器置于灰色（不會使它們消失）。代碼如下：import plotly.express as pxfig = px.scatter(pointsperplayer, x='assisted', y='notassisted', hover_name='player', hover_data=['team_name','season'], color='season')fig.show()圖形結果如下：總而言之，我想要三個過濾器，一個是賽季，另一個是球隊，另一個是球員，能夠在每個過濾器中有多個選擇，并獲得不同的顏色，其余的點變灰，這樣我就可以將結果與其他結果進行比較，我不確定是否可以使用 plotly express 或者我是否應該使用不同的庫。
1 回答
鳳凰求蠱
TA貢獻1825條經驗 獲得超4個贊
所以我無法操縱圖例，但我可以通過在此處找到的下拉小部件添加過濾器。根據您的 IDE，您可能需要使用 Jupyter 來使小部件工作。我遇到了 VSCode 無法顯示小部件的問題。我下面的功能是按球隊名稱、賽季或球員進行過濾，并在該過濾器中比較兩個選項。我希望這可以擴展以滿足您的需求。
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
import ipywidgets as ipy
from ipywidgets import Output, VBox, widgets
# First gather the data I need and choose the display colors
playerData = pd.read_csv("playerData.csv")
teamNames = list(playerData['team_name'].unique().tolist());
seasons = list(playerData['season'].unique().tolist());
players = list(playerData['player'].unique().tolist());
color1 = 'red'
color2 = 'blue'
color3 = 'gray'
# This creates the initial figure.
# Note that px.scatter generates multiple scatter plot 'traces'. Each trace contains
# the data points associated with 1 team/season/player depending on what the property
# of 'color' is set to.
trace1 = px.scatter(playerData, x='assisted', y='notassisted', color='team_name')
fig = go.FigureWidget(trace1)
# Create all our drop down widgets
filterDrop = widgets.Dropdown(
description='Filter:',
value='team_name',
options=['team_name', 'season','player']
)
teamDrop1 = widgets.Dropdown(
description='Team Name:',
value='NACIONAL',
options=list(playerData['team_name'].unique().tolist())
)
teamDrop2 = widgets.Dropdown(
description='Team Name:',
value='NACIONAL',
options=list(playerData['team_name'].unique().tolist())
)
playerDrop1 = widgets.Dropdown(
description='Player:',
value='A. DANRIDGE',
options=list(playerData['player'].unique().tolist())
)
playerDrop2 = widgets.Dropdown(
description='Player:',
value='A. DANRIDGE',
options=list(playerData['player'].unique().tolist())
)
seasonDrop1 = widgets.Dropdown(
description='Season:',
value='Season_17_18',
options=list(playerData['season'].unique().tolist())
)
seasonDrop2 = widgets.Dropdown(
description='Season:',
value='Season_17_18',
options=list(playerData['season'].unique().tolist())
)
# This will be called when the filter dropdown changes.
def filterResponse(change):
# generate the new traces that are filtered by teamname, season, or player
tempTrace = px.scatter(playerData, x='assisted', y='notassisted', color=filterDrop.value)
with fig.batch_update():
# Delete the old traces and add the new traces in one at a time
fig.data = []
for tr in tempTrace.data:
fig.add_scatter(x = tr.x, y = tr.y, hoverlabel = tr.hoverlabel, hovertemplate = tr.hovertemplate, \
legendgroup = tr.legendgroup, marker = tr.marker, mode = tr.mode, name = tr.name)
# Call response so that it will color the markers appropriately
response(change)
# This is called by all the other drop downs
def response(change):
# colorList is a list of strings the length of the # of traces
if filterDrop.value == 'team_name':
colorList = [color1 if x == teamDrop1.value else color2 if x == teamDrop2.value else color3 for x in teamNames]
elif filterDrop.value == 'season':
colorList = [color1 if x == seasonDrop1.value else color2 if x == seasonDrop2.value else color3 for x in seasons]
else:
colorList = [color1 if x == playerDrop1.value else color2 if x == playerDrop2.value else color3 for x in players]
with fig.batch_update():
# Color each trace according to our chosen comparison traces
for i in range(len(colorList)):
fig.data[i].marker.color = colorList[i]
# These determine what function should be called when a drop down changes
teamDrop1.observe(response, names="value")
seasonDrop1.observe(response, names="value")
playerDrop1.observe(response, names="value")
teamDrop2.observe(response, names="value")
seasonDrop2.observe(response, names="value")
playerDrop2.observe(response, names="value")
filterDrop.observe(filterResponse, names="value")
# HBox and VBox are used to organize the other widgets and figures
container1 = widgets.HBox([filterDrop])
container2 = widgets.HBox([teamDrop1, seasonDrop1, playerDrop1])
container3 = widgets.HBox([teamDrop2, seasonDrop2, playerDrop2])
widgets.VBox([container1, container2, container3, fig])
結果如下所示
添加回答
舉報
0/150
提交
取消