tradieboi.py

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

import pandas as pd
from scipy.signal import argrelextrema

eth = pd.read_csv("./financial_data/eth.csv")
priceData = pd.DataFrame()

priceData["price"] = eth["Value"]
priceData["date"] = eth["Date(UTC)"]

priceData.index = pd.to_datetime(priceData["date"])

n=30 # number of points to be checked before and after 
# Find local peaks
priceData['min'] = priceData.iloc[argrelextrema(priceData.price.values, np.less_equal, order=n)[0]]['price']
priceData['max'] = priceData.iloc[argrelextrema(priceData.price.values, np.greater_equal, order=n)[0]]['price']


priceDataFiltered = priceData[priceData.index >= "2016"]

# Plot results


figure, axes = plt.subplots(figsize=(30, 10)) 
plt.scatter(priceDataFiltered.index, priceDataFiltered['min'], c='r')
plt.scatter(priceDataFiltered.index, priceDataFiltered['max'], c='g')
plt.plot(priceDataFiltered.index, priceDataFiltered['price'])


axes.xaxis.set_major_locator(mdates.MonthLocator())
axes.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m')) 
axes.tick_params(axis='x', rotation=45)

plt.show()