从上面的折线图可以看出，它只是 matplotlib.show 的 x 轴从最旧到最新，但 mplfinance ohlc 从最新到最旧。我相信这是因为索引从最新到最旧。
那么如何反转 mplfinance 的索引呢？
我正在为 ohlc 图表使用 pandas 数据框。
这是代码：
def runCandles(user_symbol):
openarr = []
closearr = []
higharr = []
lowarr = []
datesarr = []
ha_close_arr = []
ha_open_arr = []
ha_high_arr = []
ha_low_arr = []
symbol = user_symbol
response = requests.get("https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol="+symbol+"&apikey=")
responsedata = response.json()
#pass response json as data
def get_ohlc(data):
for value in data['Time Series (Daily)']:
date = datetime.strptime(value,'%Y-%m-%d')
open = float(responsedata['Time Series (Daily)'][value]['1. open'])
close = float(responsedata['Time Series (Daily)'][value]['4. close'])
high = float(responsedata['Time Series (Daily)'][value]['2. high'])
low = float(responsedata['Time Series (Daily)'][value]['3. low'])
openarr.append(open)
closearr.append(close)
lowarr.append(low)
higharr.append(high)
datesarr.append(date)
def get_ha_ohlc():
if (len(openarr) == len(closearr) == len(lowarr) == len(higharr) == len(datesarr)):
length = len(openarr)
count = 0
while count < length:
ha_close = 0.25*(openarr[count]+closearr[count]+lowarr[count]+higharr[count])
ha_close_arr.append(ha_close)
ha_open = 0.5*(openarr[count-1]+closearr[count-1])
ha_open_arr.append(ha_open)
ha_high = max(openarr[count],closearr[count],higharr[count])
ha_high_arr.append(ha_high)
ha_low = min(openarr[count],closearr[count],lowarr[count])
ha_low_arr.append(ha_low)
count += 1
get_ohlc(responsedata)
get_ha_ohlc()
reformatted_data = dict()
reformatted_data["Date"] = []
reformatted_data["Open"] = []
reformatted_data["High"] = []
reformatted_data["Close"] = []
reformatted_data["Low"] = []
reformatted_data["Date"] = datesarr
reformatted_data["Open"] = ha_open_arr
reformatted_data["High"] = ha_high_arr
reformatted_data["Close"] = ha_close_arr
reformatted_data["Low"] = ha_low_arr
df = pd.DataFrame.from_dict(reformatted_data)
print(df)
df.set_index('Date', inplace=True)
# df.reindex(index=df.index[::-1])
print(df)
# df.head(3)
plt.plot(datesarr, ha_close_arr)
plt.show()
mpf.plot(df)
# print(datesarr)
# print(list(reversed(datesarr)))
这是数据：
Date,Open,High,Close,Low
2020-09-23,19.755000000000003,22.219,21.089775000000003,20.1901
2020-09-22,20.975,22.06,21.6096,21.1884
2020-09-21,21.595,22.09,21.53,21.11
2020-09-18,21.46,23.04,22.549999999999997,22.18
2020-09-17,22.490000000000002,23.54,22.457499999999996,21.72
2020-09-16,22.285,23.54,23.0175,22.66
2020-09-15,22.935,24.6,23.839999999999996,23.25
2020-09-14,23.755,24.15,23.428325,22.9233
2020-09-11,23.32,23.49,22.98,22.37
2020-09-10,23.03,24.49,23.609999999999996,23.07
2020-09-09,23.439999999999998,24.97,23.87,23.25
2020-09-08,23.630000000000003,24.77,23.27,22.55
2020-09-04,22.88,27.0,25.235,22.56
2020-09-03,25.689999999999998,29.15,27.3675,25.8
2020-09-02,27.259999999999998,34.4234,32.57085,30.61
2020-09-01,32.625,31.0,29.4275,27.8
2020-08-31,29.455,29.639,28.42975,26.75
2020-08-28,28.665,28.98,28.0192,27.1768
2020-08-27,27.96,28.97,27.52,26.7
2020-08-26,27.205,28.48,27.497500000000002,26.51
2020-08-25,27.5,29.42,28.61,27.11
2020-08-24,28.955,29.96,28.93,27.85
2020-08-21,28.955,27.2,25.560000000000002,24.42
2020-08-20,25.310000000000002,24.45,23.235,22.2
2020-08-19,23.145,21.66,20.785,20.0
2020-08-18,20.74,20.8,19.915000000000003,19.1
2020-08-17,19.880000000000003,19.43,19.167499999999997,18.81
2020-08-14,19.215,20.49,19.6075,18.68
2020-08-13,19.630000000000003,19.6,18.9625,18.31
2020-08-12,18.97,21.19,20.2725,19.25