I made a new pandas DataFrame by adding the last 15 items, minus the last item, from the binance historical. And every minute I add the new data to the newly made DataFrame. This works great and gives the following output after a few minutes:
open close ... high time
0 61095.98000000 61099.44000000 ... 61115.93000000 2021-11-05 15:34:00
1 61099.45000000 61038.01000000 ... 61104.11000000 2021-11-05 15:35:00
2 61038.00000000 61010.96000000 ... 61080.05000000 2021-11-05 15:36:00
3 61010.97000000 60978.94000000 ... 61017.93000000 2021-11-05 15:37:00
4 60977.80000000 60945.65000000 ... 60990.54000000 2021-11-05 15:38:00
5 60945.65000000 60900.00000000 ... 60958.00000000 2021-11-05 15:39:00
6 60900.00000000 60991.44000000 ... 60993.71000000 2021-11-05 15:40:00
7 60991.45000000 60888.04000000 ... 60996.14000000 2021-11-05 15:41:00
8 60888.04000000 60880.94000000 ... 60906.98000000 2021-11-05 15:42:00
9 60880.95000000 60810.99000000 ... 60880.95000000 2021-11-05 15:43:00
10 60810.99000000 60763.94000000 ... 60864.74000000 2021-11-05 15:44:00
11 60763.95000000 60872.14000000 ... 60896.86000000 2021-11-05 15:45:00
12 60873.17000000 60908.84000000 ... 60934.22000000 2021-11-05 15:46:00
13 60908.84000000 60844.19000000 ... 60914.94000000 2021-11-05 15:47:00
14 60844.18000000 60870.40000000 ... 60879.34000000 2021-11-05 15:48:00
15 60870.39000000 60845.01000000 ... 60877.53000000 2021-11-05 15:49:00
16 60845.02000000 60900.62000000 ... 60920.64000000 2021-11-05 15:50:00
17 60900.63000000 60873.40000000 ... 60901.29000000 2021-11-05 15:51:00
[18 rows x 5 columns]
Now I want to add the stochastic oscillator to this DataFrame. I tried this by adding the following line to my code:
df.ta.stoch(high='high', low='low', k=14, d=3, append=True)
However after adding this code, my DataFrame won't show anymore by the print statement and neither does the stochastic when I try to print it. How do I make the stochastic work with my self made DataFrame? If you have any questions, ask away! Thanks in advance!
My full code below:
#import threading
import pandas_ta as ta
import websocket
import json
import pandas as pd
from binance import Client
client = Client('5Z5VtpcArDgm525AC6sUoy8TJer4tlel4Twt1ENf7OIzeLB2qx6oaLICHL9jVKoa', 'e641miivoiguEU3gOKjuYEvVKdFNazehtovZtJKdQXb2NVxwTeo1AQ2TBDArocWU')
historical = client.get_historical_klines('BTCUSDT', Client.KLINE_INTERVAL_1MINUTE, '11/05/2021', limit=1000)
SOCKET = "wss://stream.binance.com:9443/ws/btcusdt@kline_1m"
hist_df = pd.DataFrame(historical)
hist_df.columns = ['Open time','Open', 'High', 'Low', 'Close', 'Volume', 'Close time', 'Quote Asset Volume', 'Number of trades', 'TB Base volume','Tb Quote volume','Ignore']
def on_open(ws):
print('opened connection')
def on_close(ws):
print('closed connection')
dic = {'open': [], 'close': [], 'low': [], 'high': [], 'time': []}
history_open_price = hist_df['Open'][-15:-1]
history_close_price = hist_df['Close'][-15:-1]
history_highest_price = hist_df['High'][-15:-1]
history_lowest_price = hist_df['Low'][-15:-1]
history_time = pd.to_datetime(hist_df['Open time']/1000, unit='s')[-15:-1]
for a, b in history_open_price.items():
dic['open'].append(b)
for a, b in history_close_price.items():
dic['close'].append(b)
for a, b in history_highest_price.items():
dic['high'].append(b)
for a, b in history_lowest_price.items():
dic['low'].append(b)
for a, b in history_time.items():
dic['time'].append(str(b))
def on_message(ws, message):
json_message = json.loads(message)
candle = json_message['k']
open_price = candle['o']
close_price = candle['c']
highest_price = candle['h']
lowest_price = candle['l']
status = candle['x']
open_time = pd.to_datetime(candle['t']/1000, unit='s')
if status:
dic['open'].append(open_price)
dic['close'].append(close_price)
dic['high'].append(highest_price)
dic['low'].append(lowest_price)
dic['time'].append(str(open_time))
df = pd.DataFrame(dic)
# df.ta.stoch(high='high', low='low', k=14, d=3, append=True)
print(df)
ws = websocket.WebSocketApp(SOCKET, on_open=on_open, on_close=on_close, on_message=on_message)
ws.run_forever()
