#!/usr/bin/env python
# coding: utf-8

# In[128]:


import time, requests
# 取得件数
count = 5
# 現在時刻と取得開始時刻
to_time   = int(time.time())
from_time = to_time - (count - 1) * 60
# OHLCVデータ取得
param = {"period": 1, "from": from_time, "to": to_time}
url   = "https://www.bitmex.com/api/udf/history?symbol=XBTUSD&resolution={period}&from={from}&to={to}".format(**param)
d     = requests.get(url).json()
# 取得結果を表示(json:dict0)
display(d, type(d))

# requestで取得したjson結果はOHLCVの各列がリストとなっている
print("timestamp :", d["t"], type(d["t"]))
print("open      :", d["o"], type(d["o"]))
print("high      :", d["h"], type(d["h"]))
print("low       :", d["l"], type(d["l"]))
print("close     :", d["c"], type(d["c"]))
print("volume    :", d["v"], type(d["v"]))


# In[129]:


# 各列リストからOHLCV二次元配列を作成

# for文
lst_ohlcv =[]
for i in range(len(d["t"])):
    ohlcv = [d["t"][i], d["o"][i], d["h"][i], d["l"][i], d["c"][i], d["v"][i]]
    lst_ohlcv.append(ohlcv)
display(lst_ohlcv, type(lst_ohlcv))

# リスト内包表記
lst_ohlcv2 = [list(ohlcv) for ohlcv in zip(d["t"], d["o"], d["h"], d["l"], d["c"], d["v"])]
display(lst_ohlcv2, type(lst_ohlcv2))


# In[130]:


# OHLCV二次元配列からデータ取得

print("最新足のOHLCVリストを取得")
lst_newest = lst_ohlcv[-1]
print(lst_newest, type(lst_newest))

print("\n最も古い終値を取得")
oldest_close = lst_ohlcv[0][4]
print(oldest_close, type(oldest_close))

print("\n始値リストを取得")
lst_open = [ohlcv[1] for ohlcv in lst_ohlcv]
print(lst_open, type(lst_open))

print("\n新⇒古順のOHLCVリストを取得(反転)")
lst_reverse = lst_ohlcv[::-1]
display(lst_reverse, type(lst_reverse))


# In[131]:


import pandas as pd
import numpy as np
# リスト⇒Series
sr_timestamp = pd.Series(d["t"])
sr_open      = pd.Series(d["o"])
sr_high      = pd.Series(d["h"])
sr_low       = pd.Series(d["l"])
sr_close     = pd.Series(d["c"])
sr_volume    = pd.Series(d["v"])
print(sr_timestamp, type(sr_timestamp))
print(sr_open, type(sr_open))
print(sr_high, type(sr_high))
print(sr_low, type(sr_low))
print(sr_close, type(sr_close))
print(sr_volume, type(sr_volume))


# In[132]:


# Series⇒リスト
lst_t = sr_timestamp.tolist()
lst_o = sr_open.tolist()
lst_h = sr_high.tolist()
lst_l = sr_low.tolist()
lst_c = sr_close.tolist()
lst_v = sr_volume.tolist()
print("timestamp :", lst_t, type(lst_t))
print("open      :", lst_o, type(lst_o))
print("high      :", lst_h, type(lst_h))
print("low       :", lst_l, type(lst_l))
print("close     :", lst_c, type(lst_c))
print("volume    :", lst_v, type(lst_v) ,"\n")

# Series⇒ndarray
nda_t = sr_timestamp.values
nda_o = sr_open.values
nda_h = sr_high.values
nda_l = sr_low.values
nda_c = sr_close.values
nda_v = sr_volume.values
print("timestamp :", nda_t, type(nda_t))
print("open      :", nda_o, type(nda_o))
print("high      :", nda_h, type(nda_h))
print("low       :", nda_l, type(nda_l))
print("close     :", nda_c, type(nda_c))
print("volume    :", nda_v, type(nda_v))


# In[133]:


from collections import OrderedDict
# DataFrame作成

# OHLCV二次元配列⇒DataFrame
df_ohlcv = pd.DataFrame(lst_ohlcv,
                        columns=["timestamp", "open", "high", "low", "close", "volume"])
display(df_ohlcv, type(df_ohlcv))

# OrderedDict⇒DataFrame
df_ohlcv2 = pd.DataFrame(OrderedDict({
    "timestamp" : d["t"],
    "open"      : d["o"],
    "high"      : d["h"],
    "low"       : d["l"],
    "close"     : d["c"],
    "volume"    : d["v"],
}))
display(df_ohlcv2, type(df_ohlcv2))


# In[134]:


# DataFrameからデータ取得

print("最新(最終行)の終値を取得")
last_close = df_ohlcv.iloc[-1, 4]
print(last_close, type(last_close))

print("\n最も古い(先頭)行を取得")
row_first = df_ohlcv.iloc[0] # Series
display(row_first, type(row_first))
# リスト変換
lst_first = row_first.tolist()
display(lst_first, type(lst_first))

print("終値列を取得")
col_close = df_ohlcv["close"] # Series
display(col_close, type(col_close))
# リスト変換
lst_close = col_close.tolist()
display(lst_close, type(lst_close))

print("2～4行目の時刻, 始値, 終値列の取得")
rng_toc = df_ohlcv.iloc[2:5, [0,1,4]] # DataFrame
display(rng_toc, type(rng_toc))
# リスト変換
lst_toc = rng_toc.values.tolist()
display(lst_toc, type(lst_toc))


# In[135]:


# DataFrameインデックス

print("timestampをインデックスに設定")
df_ohlcv.set_index("timestamp", inplace=True)
display(df_ohlcv)

print("timestampインデックスを解除")
df_ohlcv.reset_index(inplace=True)
display(df_ohlcv)


# In[136]:


# DataFrameデータ追加/削除

# 最終行をもう1行追加
df_new = pd.DataFrame([[0, 1, 2, 3, 4, 5]],
                      columns=["timestamp", "open", "high", "low", "close", "volume"])
df_ohlcv = df_ohlcv.append(df_new, ignore_index=True)
display(df_ohlcv)

# 最終行を1行削除
df_ohlcv.drop(len(df_ohlcv) - 1, axis=0, inplace=True)
display(df_ohlcv)

# datetime列を追加
df_ohlcv["datetime"] = pd.to_datetime(df_ohlcv["timestamp"], unit="s")
display(df_ohlcv)

# datetime列を削除
df_ohlcv.drop("datetime", axis=1, inplace=True)
display(df_ohlcv)


# In[137]:


# DataFrame列の並び替え
df_ohlcv = df_ohlcv[["open", "high", "low", "close", "volume", "timestamp"]]
display(df_ohlcv)

# DataFrame列名変更
df_ohlcv.rename(
    columns={
        "open"      : "始値",
        "high"      : "高値",
        "low"       : "安値",
        "close"     : "終値",
        "volume"    : "出来高",
        "timestamp" : "タイムスタンプ",
    }, inplace=True)
display(df_ohlcv)


# In[138]:


# DataFrame行反転
df_ohlcv = df_ohlcv.iloc[::-1]
display(df_ohlcv)

# DataFrame列反転
df_ohlcv = df_ohlcv.iloc[:, ::-1]
display(df_ohlcv)