Plotting Right extended horizontal line matplotlib

Question

I am trying to plot right extended horizontal lines using matplotlib and i have failed to find a way i need your help.

1- I have a pandas df with dates,prices and indicator values
2- i want to plot in one chart, the price as a line and also on top of the price i want to plot an extended line where my indicator values are above a threshold, the expected results is something like this picture.

The second screenshot you can see those colored circles on the price line I want to replace them with a horizontal right extended line. data.csv: https://drive.google.com/open?id=1ncTTvwJXVeh6dMHrIML7MpjlS-Yfox_o

Code snippet i am trying:

import pandas as pd 
import matplotlib.pyplot as plt

df = pd.read_csv('plot_data.csv')

BW121 = df[['BW121','Close']]
BW121 = BW121.where(BW121.BW121>70).dropna()

BW50=df[['BW50','Close']]
BW50 = BW50.where(BW50.BW50>70).dropna()

LW121 =df[['LW121','Close']]
LW121 = LW121.where(LW121.LW121>70).dropna()

LW50 = df[['LW50','Close']]
LW50 = LW50.where(LW50.LW50>70).dropna()

plt.style.use('fivethirtyeight')
plt.scatter(BW121.index,BW121['Close'], color ="green",label='BW121')
plt.scatter(BW50.index , BW50['Close'], color ="blue", s=80,label='BW50')

plt.scatter(LW121.index , LW121['Close'], color ="red", s=80,label='LW121')
plt.scatter(LW50.index , LW50['Close'], color ="orange", s=80,label='LW50')

#Price Plot
plt.plot(df.index, df['Close'], marker='',alpha = 0.5,color='green')

plt.legend(loc='upper right')
plt.show()

Answer 1

To plot a horizontal line in matplotlib you can use plt.axhline :

plt.scatter(BW50['Close'], color="blue", label='BW50')

axhline has xmin and xmax arguments if you'd rather the lines to not fill the plot horizontally.

Depending on what your specific outcome is, you could try:

import pandas as pd 
import matplotlib.pyplot as plt

df = pd.read_csv('plot_data.csv')

BW121 = df[['BW121','Close']]
BW121 = BW121.where(BW121.BW121>70).dropna()

BW50=df[['BW50','Close']]
BW50 = BW50.where(BW50.BW50>70).dropna()

LW121 =df[['LW121','Close']]
LW121 = LW121.where(LW121.LW121>70).dropna()

LW50 = df[['LW50','Close']]
LW50 = LW50.where(LW50.LW50>70).dropna()

plt.style.use('fivethirtyeight')
plt.scatter(BW121.index,BW121['Close'], color ="green",label='BW121')
plt.scatter(BW50.index , BW50['Close'], color ="blue", s=80,label='BW50')
# axhline used here, one for each 'Close' value
for i in BW50['Close']:
    plt.axhline(i, color ="blue", lw=0.5)

plt.scatter(LW121.index , LW121['Close'], color ="red", s=80,label='LW121')
plt.scatter(LW50.index , LW50['Close'], color ="orange", s=80,label='LW50')
# could repeat axhline here for other data etc.

#Price Plot
plt.plot(df.index, df['Close'], marker='',alpha = 0.5,color='green')

plt.legend(loc='upper right')
plt.show()