使用plotly进行子绘图时如何隐藏x轴值
Ben*_*oit 4 python pandas plotly
我正在使用 plotly 绘制一个大的 csv 文件（包含大量数据）并在线（实际上有效）一些图表中进行子绘制。问题是，对于每个图表，我都会获得 x 轴上每个点的所有日期+时间，从而导致图表质量不佳。如何为第 5 个图表隐藏 x 轴的值，同时保留最后一个图表的值以更好地查看图表？
这是我的代码：有问题的部分从第 125 行开始
import os
import pandas as pd
import plotly
import plotly.graph_objs as go
from tkinter import *
window = Tk()
window.title("Interface utilisateur")
consigne=Label(window, text="Merci de remplir les champs ci-dessous avant de cliquer sur start")
consigne.grid(column = 1,row=0)
consDateDEB=Label(window, text="Date de début de sélection (format JJMMAAAA)")
consDateDEB.grid(column=0,row=1)
DateDEB = Entry(window,width=25)
DateDEB.grid(column = 2,row=1)
consDateFIN=Label(window, text="Date de fin de sélection (format JJMMAAAA)")
consDateFIN.grid(column=0,row=2)
DateFIN = Entry(window,width=25)
DateFIN.grid(column = 2,row=2)
consPathIN=Label(window, text="Chemin d'accès aux fichiers (format C://user/dossier1/dossier2/)")
consPathIN.grid(column=0,row=3)
PathIN = Entry(window,width=50)
PathIN.grid(column = 2,row=3)
consPathOUT=Label(window, text="Chemin d'écriture des fichiers (format C://user/dossier1/dossier2/)")
consPathOUT.grid(column=0,row=4)
PathOUT = Entry(window,width=50)
PathOUT.grid(column = 2,row=4)
def click():
pathIN = PathIN.get()
pathOUT = PathOUT.get()
DateDebut = DateDEB.get()
DateFin = DateFIN.get()
tracer(DateDebut,DateFin,pathIN,pathOUT)
btn = Button(window, text='Start',command=click,width=30,height=2,activebackground='red')
btn.grid(column = 1,row=5)
window.mainloop()
def tracer(DateDebut,DateFin,pathIN,pathOUT):
# DateDebut=10052019
# DateFin=12052019
# pathIN='D://Clef64go/PJT/Logfiles/'
# pathOUT='D://Clef64go/PJT/OUT/'
Logfiles = os.listdir(pathIN)
def conversion(Logfile_JJMMAAAA):
nomFichierINT = int(Logfile_JJMMAAAA[12:16] + Logfile_JJMMAAAA[10:12] + Logfile_JJMMAAAA[8:10])
return nomFichierINT
def conversionInverse(AAAAMMJJ):
AAAAMMJJ = str(AAAAMMJJ)
nomFichierSTR = "Logfile_" + AAAAMMJJ[6:8] + AAAAMMJJ[4:6] + AAAAMMJJ[0:4]+".csv"
return nomFichierSTR
DateDebut = str(DateDebut)
DateFin = str(DateFin)
DebTempo = DateDebut[4:8]+DateDebut[2:4]+DateDebut[0:2]
FinTempo = DateFin[4:8]+DateFin[2:4]+DateFin[0:2]
DateDebut=int(DebTempo)
DateFin=int(FinTempo)
L_Selection=[]
for fichier in Logfiles:
Tempo=conversion(fichier)
if Tempo >= DateDebut and Tempo <= DateFin :
L_Selection.append(Tempo)
L_Selection = sorted(L_Selection)
L_Clean=[]
for fichier in L_Selection :
Tempo = conversionInverse(fichier)
L_Clean.append(Tempo)
#L_Log = os.listdir("D://Clef64go/PJT/TEST2/")
dfList=[]
colnames=['No.','Date','Time','Temp1','Unit','Temp2','Unit','Lux2','Unit','BP1','Humidité Relat','Unit','CO2','Unit','Présence','Temp1_EnO','Unit','Temp2_EnO','Unit','Temp3_EnO','Unit','RH3_EnO','Unit','Chauffage','test']
for filename in L_Clean:
filename = pathIN + filename
typefile=type(filename)
df=pd.read_csv(filename, sep = ';', error_bad_lines=False, encoding="ANSI")
dfList.append(df)
concatDf=pd.concat(dfList,axis=0)
concatDf.columns=colnames
pathOUT = pathOUT + "/" + str(DateDebut) +" a "+ str(DateFin) + ".csv"
concatDf.to_csv(pathOUT, sep = ';',index=False)
df = pd.read_csv(pathOUT,decimal=",",sep = ';', error_bad_lines=False, encoding="ANSI",names=colnames)
df['Temp1'] = [x.replace(',', '.') for x in df['Temp1']]
df['Temp2'] = [x.replace(',', '.') for x in df['Temp2']]
df['Temp1_EnO'] = [x.replace(',', '.') for x in df['Temp1_EnO']]
df['Temp2_EnO'] = [x.replace(',', '.') for x in df['Temp2_EnO']]
df['Temp3_EnO'] = [x.replace(',', '.') for x in df['Temp3_EnO']]
date = df['Date']+df['Time']
y1 = df['Temp1']
y2 = df['Temp2']
y3 = df['Temp3_EnO']
y4 = df['Humidité Relat']
y5 = df['CO2']
y6 = df['Présence']
#plotly.offline.plot({
# "data": [go.Scatter(x=x, y=y)],
# "layout": go.Layout(title="Température 1 en fonction du temps")
# }, auto_open=True)
temp1 = go.Scatter(
x=date,
y=y1,
name="Température 1 (°C)"
)
temp2 = go.Scatter(
x=date,
y=y2,
name="Température 2 (°C)"
)
temp3 = go.Scatter(
x=date,
y=y3,
name="Température 3 (°C)"
)
Humidite = go.Scatter(
x=date,
y=y4,
name="Humidité relative (%)"
)
dioxyde_de_carbone = go.Scatter(
x=date,
y=y5,
name="Taux C02 (ppm)"
)
presence = go.Scatter(
x=date,
y=y6,
name="Présence"
)
fig = plotly.tools.make_subplots(rows=6, cols=1)
fig.append_trace(temp1, 1, 1)
fig.append_trace(temp2, 2, 1)
fig.append_trace(temp3, 3, 1)
fig.append_trace(Humidite, 4, 1)
fig.append_trace(dioxyde_de_carbone, 5, 1)
fig.append_trace(presence, 6, 1)
fig['layout'].update(title='Représentation graphique des données')
plotly.offline.plot(fig, filename=str(DateDebut) +" a "+ str(DateFin) + ".csv", auto_open=True)
这是我得到的：
小智 9
你可以用这两行来修复它：
fig.update_xaxes(showticklabels=False) # hide all the xticks
fig.update_xaxes(showticklabels=True, row=6, col=1)
我是从安卓评论开始的。但相关来源是这样的：
trace0 = go.Scatter(
x = [0,1,1,0,0,1,1,2,2,3,3,2,2,3],
y = [0,0,1,1,3,3,2,2,3,3,1,1,0,0]
)
trace1 = go.Scatter(
x = [0,1,2,3],
y = [1,2,4,8],
yaxis = "y2"
)
layout = go.Layout(
width = 800,
height = 500,
title = "fixed-ratio axes",
xaxis = dict(
nticks = 10,
domain = [0, 0.45],
title = "shared X axis"
),
yaxis = dict(
scaleanchor = "x",
domain = [0, 0.45],
title = "1:1"
),
yaxis2 = dict(
scaleanchor = "x",
scaleratio = 0.2,
domain = [0.55,1],
title = "1:5"
))
解释
您需要定义一次 xaxis。对于您设置的每个其他子图scaleanchor = "x"，以便每个子图共享相同的内容xaxis。所有共享一个 xasis 的图都会自动绘制为子图，因此您可以摆脱当前的结构。
需要编辑
data = [temp1,temp2,temp3,Humidite, dioxyde_de_carbone, presence]
layout = go.Layout(
width = 800,
height = 500,
title = "fixed-ratio axes using 10 ticks",
xaxis = dict(
nticks = 10,
title = "shared X axis showing DATE"
),
yaxis = dict(
scaleanchor = "x",
title = "Temp"
),
yaxis2 = dict(
scaleanchor = "x",
title = "Humidity"
),
yaxis3 = dict(
scaleanchor = "x",
title = "ppm"
),
yaxis4 = dict(
scaleanchor = "x",
title = "presence"
),
showlegend= False
)
fig = go.Figure(data=data, layout=layout)
plotly.offline.plot(fig, filename=str(DateDebut) +" a "+ str(DateFin) + ".csv", auto_open=True)
fig = plotly.tools.make_subplots(rows=6, cols=1)