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[英]Plotting pandas dataframe with boolean categorical time-series data
[英]Plotting time-series data from pandas results in ValueError
我正在使用pandas
DataFrame 和matplotlib
在同一圖中繪制三條線。 數據應該是正確的,但是當我嘗試繪制線條時,代碼返回一個ValueError
,這是意外的。
詳細錯誤警告說: ValueError: view limit minimum -105920.979 is less than 1 and is an invalid Matplotlib date value
。 如果您將非日期時間值傳遞給具有日期時間單位的軸,則通常會發生這種情況
如何修復此錯誤,並在同一圖中繪制三條線?
import pandas as pd
import datetime as dt
import pandas_datareader as web
import matplotlib.pyplot as plt
from matplotlib import style
import matplotlib.ticker as ticker
spot=pd.read_excel('https://www.eia.gov/dnav/pet/hist_xls/RWTCd.xls',sheet_name='Data 1',skiprows=2) #this is spot price data
prod=pd.read_excel('https://www.eia.gov/dnav/pet/hist_xls/WCRFPUS2w.xls',sheet_name='Data 1',skiprows=2) #this is production data
stkp=pd.read_excel('https://www.eia.gov/dnav/pet/hist_xls/WTTSTUS1w.xls',sheet_name='Data 1',skiprows=2) #this is stockpile data
fig,ax = plt.subplots()
ax.plot(spot,label='WTI Crude Oil Price')
ax.plot(prod,label='US Crude Oil Production')
ax.plot(stkp,label='US Crude Oil Stockpile')
plt.legend()
plt.show()
print(spot,prod,stkp)
matplotlib
和pandas
。conda update --all
'Date'
列解析為'Date'
並將其設置為索引。yscale
設置為'log'
,因為數字范圍很大。import pandas as pd
import matplotlib.pyplot as plt
spot=pd.read_excel('https://www.eia.gov/dnav/pet/hist_xls/RWTCd.xls', sheet_name='Data 1',skiprows=2, parse_dates=['Date'], index_col='Date') #this is spot price data
prod=pd.read_excel('https://www.eia.gov/dnav/pet/hist_xls/WCRFPUS2w.xls', sheet_name='Data 1',skiprows=2, parse_dates=['Date'], index_col='Date') #this is production data
stkp=pd.read_excel('https://www.eia.gov/dnav/pet/hist_xls/WTTSTUS1w.xls', sheet_name='Data 1',skiprows=2, parse_dates=['Date'], index_col='Date') #this is stockpile data
fig,ax = plt.subplots()
ax.plot(spot, label='WTI Crude Oil Price')
ax.plot(prod, label='US Crude Oil Production')
ax.plot(stkp, label='US Crude Oil Stockpile')
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')
plt.yscale('log')
plt.show()
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