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NoahVerner
Asked: 2022-07-29 18:04:27 +0800 CST 2022-07-29 18:04:27 +0800 CST

How to plot 2 specific data points on a price action chart using matplotlib in Python?

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Suppose I have the following chart:

btcusdt price action from 2022-04-01 05:59:59.99 to 2022-05-13 21:59:59.99

Said graph was created using the following Python code:

from binance.client import Client
import pandas as pd
import matplotlib.pyplot as plt

#personal API key and Secret Key from your Binance account

api_key = "your binance api key"
secret_key = "your binance secret key"

client = Client(api_key= api_key, api_secret= secret_key, tld= "com")

klines_btcusdt = client.get_historical_klines(symbol="BTCUSDT", interval="1h", start_str = "1648807200000", end_str="1653667199999")

df_btcusdt = pd.DataFrame(klines_btcusdt)

#drop unnecesary columns
df_btcusdt.drop(5, inplace = True, axis=1)
df_btcusdt.drop(7, inplace = True, axis=1)
df_btcusdt.drop(8, inplace = True, axis=1)
df_btcusdt.drop(9, inplace = True, axis=1)
df_btcusdt.drop(10, inplace = True, axis=1)
df_btcusdt.drop(11, inplace = True, axis=1)

# Rename the column names for best practices
df_btcusdt.rename(columns = { 0 : 'Start Date', 
                          1 : 'Open Price',
                          2 : 'High Price',
                          3 : 'Low Price',
                          4 :'Close Price',
                          6 :'End Date',
                          }, inplace = True)

# Convert Unix Time values to actual dates
df_btcusdt['Start Date'] = pd.to_datetime(df_btcusdt['Start Date'], unit='ms')
df_btcusdt['End Date'] = pd.to_datetime(df_btcusdt['End Date'], unit='ms')
df_btcusdt = df_btcusdt[['End Date','Close Price']]
df_btcusdt = df_btcusdt.set_index('End Date', inplace=False)
df_btcusdt = df_btcusdt.astype({'Close Price': 'float'})

#visualising the price
plt.figure(figsize=(8, 6), dpi=80)
plt.title('BTCUSDT Price')
plt.rc('xtick', labelsize = 8)
plt.plot(df_btcusdt.index[0:], df_btcusdt[0:])

And I am interested in marking 2 specific data points that are: df_btcusdt[0:1]and df_btcusdt[1024:1025], that is:

                         Close Price
End Date                            
2022-04-01 05:59:59.999     44646.16

                         Close Price
End Date                            
2022-05-13 21:59:59.999     30046.65

But I don't know how to do it, I tried changing the last line of my code to the following:

plt.plot(df_btcusdt.index[0:], df_btcusdt[0:], markevery = [44646.16, 30046.65], marker="ro")

but I get:

ValueError: markevery=[44646.16, 30046.65] is iterable but not a valid numpy fancy index

It should return something like this:

desired graph

Can I get help please?

python-3.x

1 Answers

  1. Best Answer

    Good day,

    You only have to obtain a list with the values ​​of "X" and "Y" that you want to mark and graph them with matplotlib.pyplot.plot.

    The styles available by default can be reviewed in matplotlib.markers.MarkerStyle.

    Generic example (For security reasons you avoided putting your keys and I can't generate the same data you have, so I did something generic):

    import numpy as np
import matplotlib.pyplot as plt

X = np.array(
    [  99912.5,   99925. ,   99937.5,   99950. ,   99962.5,   99975. ,
       99987.5,  100000. ,  100012.5,  100025. ,  100037.5,  100050. ,
       100062.5,  100075. ,  100087.5,  100100. ])
Y = np.array(
    [-83.99371  , -81.08232  , -71.8163   , -71.90387  , -79.6107   ,
     -80.90104  , -14.79405  ,   3.740311 ,  -0.6665535, -78.68803  ,
     -81.49953  , -79.48487  , -74.36191  , -80.68216  , -79.98886  ,
     -83.16663  ])

plt.title("Gráfica X Y")
plt.xlabel("Valores en X")
plt.ylabel("Valores en Y")
plt.plot(X, Y)

#Creamos una lista con los elementos que deseamos marcar
#En este caso serían los índices 7 y 9 de los arreglos X y Y
x = X[[7,9]]
y = Y[[7,9]]

#Graficar las marcas
plt.plot([x], [y], 'v', color='red', ms=10)

#Mostrar el valor numérico
for i, j in zip(x, y):
    plt.text(i, j, "({:0.2f}, {:0.2f})".format(i, j))

    This produces:

    Graph

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