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manuelinfosec/historical_klines.ipynb

Created June 26, 2022 14:11
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historical_klines.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/manuelinfosec/fe9a77f74a234d281526249416143b15/historical_klines.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9d5b8bad",
"metadata": {
"id": "9d5b8bad"
},
"outputs": [],
"source": [
"import requests\n",
"import json\n",
"import datetime as dt\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6fcb702d",
"metadata": {
"id": "6fcb702d"
},
"outputs": [],
"source": [
"url = 'https://api.binance.com/'\n",
"endpoint = 'api/v3/klines'\n",
"\n",
"base = 'BTC'\n",
"quote = 'USDT' \n",
"\n",
"symbol = base+quote\n",
"interval = '1d'\n",
"limit = 1000\n",
"\n",
"start = dt.datetime(2020,1,1); end = dt.datetime(2020,2,1)\n",
"startTime = int(dt.datetime.timestamp(start)*1000); endTime = int(dt.datetime.timestamp(end)*1000)\n",
"\n",
"fromtime = lambda time: dt.datetime.fromtimestamp(time[0]/1000).strftime('%a %d %b, %Y %H:%M:%S')\n",
"totime = lambda time: dt.datetime.fromtimestamp(time[6]/1000).strftime('%a %d %b, %Y %H:%M:%S')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "59e923b2",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "59e923b2",
"outputId": "5a2f4714-9d76-4368-8c05-0a05438ecd58"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
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'7795.34000000', '7346.76000000', '7758.00000000', '54635.69531600', 1578355199999, '413330481.22604919', 449937, '28853.76777000', '218411610.65942464', '0'], [1578355200000, '7758.90000000', '8207.68000000', '7723.71000000', '8145.28000000', '91171.68466100', 1578441599999, '724202791.14296263', 685315, '46192.11154900', '366866967.61393177', '0'], [1578441600000, '8145.92000000', '8455.00000000', '7870.00000000', '8055.98000000', '112622.64264000', 1578527999999, '926410232.60450582', 830375, '55071.10951400', '453284250.45453957', '0'], [1578528000000, '8054.72000000', '8055.96000000', '7750.00000000', '7817.76000000', '64239.51983000', 1578614399999, '507258250.47487964', 478800, '31645.75922100', '249899679.33440103', '0'], [1578614400000, '7817.74000000', '8199.00000000', '7672.00000000', '8197.02000000', '82406.77744800', 1578700799999, '652774220.38843703', 606101, '42361.75530700', '335845385.67483303', '0'], [1578700800000, '8198.86000000', '8286.34000000', '8003.16000000', '8020.01000000', '54810.03266700', 1578787199999, '445034349.56470204', 469131, '27916.12497400', '226716001.44288607', '0'], [1578787200000, '8020.01000000', '8197.00000000', '7960.00000000', '8184.98000000', '38131.49433600', 1578873599999, '309351920.45885002', 350662, '19718.54109600', '159972663.99291870', '0'], [1578873600000, '8184.97000000', '8196.00000000', '8055.89000000', '8110.34000000', '31159.75568300', 1578959999999, '252656965.35815013', 289144, '15215.22650100', '123407351.91807934', '0'], [1578960000000, '8110.34000000', '8880.00000000', '8105.54000000', '8810.01000000', '120399.12674200', 1579046399999, '1032735180.86587384', 915328, '62492.09667600', '536081638.05418570', '0'], [1579046400000, '8814.64000000', '8916.48000000', '8564.00000000', '8821.41000000', '84816.29760600', 1579132799999, '743712237.27908164', 764048, '42493.55102600', '372770745.17929917', '0'], [1579132800000, '8820.01000000', '8859.81000000', '8586.00000000', '8720.01000000', '51991.07428400', 1579219199999, '451752380.28108111', 543064, '25996.30135000', '225914888.37777233', '0'], [1579219200000, '8720.15000000', '9041.65000000', '8672.44000000', '8913.28000000', '70897.73737700', 1579305599999, '629568740.70700897', 676403, '36139.80884500', '320997160.95891669', '0'], [1579305600000, '8913.27000000', '8988.88000000', '8806.38000000', '8915.96000000', '38294.74654500', 1579391999999, '340852837.91608031', 458182, '19421.29531300', '172895403.23974317', '0'], [1579392000000, '8915.09000000', '9198.98000000', '8466.00000000', '8701.70000000', '70676.88925900', 1579478399999, '623950864.27629280', 615665, '33655.94324100', '297282818.09315907', '0'], [1579478400000, '8701.72000000', '8746.99000000', '8521.28000000', '8642.35000000', '38896.63974600', 1579564799999, '336447837.00180591', 385006, '19453.86378200', '168293007.48754648', '0'], [1579564800000, '8642.35000000', '8789.00000000', '8488.00000000', '8736.03000000', '36494.68765900', 1579651199999, '316056704.98473800', 365621, '18731.87163700', '162303157.94279355', '0'], [1579651200000, '8736.04000000', '8818.00000000', '8590.00000000', '8682.36000000', '29080.55713800', 1579737599999, '252638888.21492550', 317424, '14477.15751200', '125794389.99554266', '0'], [1579737600000, '8682.77000000', '8691.81000000', '8306.39000000', '8404.52000000', '48165.94459700', 1579823999999, '407428808.67533703', 464805, '23287.71244400', '196965082.04041370', '0'], [1579824000000, '8404.52000000', '8528.02000000', '8238.00000000', '8439.00000000', '41687.52952900', 1579910399999, '349874174.79003938', 407271, '21293.48958600', '178752179.11477745', '0'], [1579910400000, '8438.99000000', '8451.26000000', '8254.90000000', '8340.58000000', '25521.15793200', 1579996799999, '212869245.63589778', 283118, '13076.75278600', '109098245.22427255', '0'], [1579996800000, '8340.01000000', '8618.13000000', '8293.66000000', '8615.00000000', '31130.48516400', 1580083199999, '263941925.27299900', 332612, '15797.91126700', '133936210.14356350', '0'], [1580083200000, '8614.39000000', '9000.00000000', '8535.00000000', '8907.57000000', '53973.54299600', 1580169599999, '473194952.80446884', 514196, '28592.32652100', '250794158.80919072', '0'], [1580169600000, '8907.57000000', '9400.00000000', '8862.40000000', '9374.21000000', '74584.85376500', 1580255999999, '676593159.48233962', 616678, '38852.36324600', '352558461.21538207', '0'], [1580256000000, '9375.34000000', '9449.24000000', '9216.00000000', '9301.53000000', '53864.06512200', 1580342399999, '503188568.83635783', 492545, '26615.65132900', '248688826.41119043', '0'], [1580342400000, '9301.57000000', '9578.00000000', '9204.44000000', '9513.21000000', '60626.74425900', 1580428799999, '569652869.81968368', 529570, '30852.55545000', '290043577.43928681', '0'], [1580428800000, '9511.52000000', '9530.22000000', '9210.01000000', '9352.89000000', '45552.02235200', 1580515199999, '425779010.40653666', 428547, '22482.47089900', '210150300.22227438', '0'], [1580515200000, '9351.71000000', '9464.53000000', '9281.00000000', '9384.61000000', '28578.06735400', 1580601599999, '268137739.99333750', 334972, '14679.12630500', '137764121.89168733', '0']]\n"
]
}
],
"source": [
"href = f\"{url}{endpoint}?symbol={symbol}&interval={interval}&startTime={startTime}&endTime={endTime}&limit={limit}\"\n",
"\n",
"data = requests.get(href).json()\n",
"open_times = list(map(fromtime, data)); close_times = list(map(totime,data))\n",
"\n",
"print(data)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f5d7078b",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "f5d7078b",
"outputId": "3cb43300-89c8-47cd-a479-e2c17c0412fc"
},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" OpenTime Open High Low Close \\\n",
"0 Wed 01 Jan, 2020 00:00:00 7195.24 7255.00 7175.15 7200.85 \n",
"1 Thu 02 Jan, 2020 00:00:00 7200.77 7212.50 6924.74 6965.71 \n",
"2 Fri 03 Jan, 2020 00:00:00 6965.49 7405.00 6871.04 7344.96 \n",
"3 Sat 04 Jan, 2020 00:00:00 7345.00 7404.00 7272.21 7354.11 \n",
"4 Sun 05 Jan, 2020 00:00:00 7354.19 7495.00 7318.00 7358.75 \n",
"5 Mon 06 Jan, 2020 00:00:00 7357.64 7795.34 7346.76 7758.00 \n",
"6 Tue 07 Jan, 2020 00:00:00 7758.90 8207.68 7723.71 8145.28 \n",
"7 Wed 08 Jan, 2020 00:00:00 8145.92 8455.00 7870.00 8055.98 \n",
"8 Thu 09 Jan, 2020 00:00:00 8054.72 8055.96 7750.00 7817.76 \n",
"9 Fri 10 Jan, 2020 00:00:00 7817.74 8199.00 7672.00 8197.02 \n",
"10 Sat 11 Jan, 2020 00:00:00 8198.86 8286.34 8003.16 8020.01 \n",
"11 Sun 12 Jan, 2020 00:00:00 8020.01 8197.00 7960.00 8184.98 \n",
"12 Mon 13 Jan, 2020 00:00:00 8184.97 8196.00 8055.89 8110.34 \n",
"13 Tue 14 Jan, 2020 00:00:00 8110.34 8880.00 8105.54 8810.01 \n",
"14 Wed 15 Jan, 2020 00:00:00 8814.64 8916.48 8564.00 8821.41 \n",
"15 Thu 16 Jan, 2020 00:00:00 8820.01 8859.81 8586.00 8720.01 \n",
"16 Fri 17 Jan, 2020 00:00:00 8720.15 9041.65 8672.44 8913.28 \n",
"17 Sat 18 Jan, 2020 00:00:00 8913.27 8988.88 8806.38 8915.96 \n",
"18 Sun 19 Jan, 2020 00:00:00 8915.09 9198.98 8466.00 8701.70 \n",
"19 Mon 20 Jan, 2020 00:00:00 8701.72 8746.99 8521.28 8642.35 \n",
"20 Tue 21 Jan, 2020 00:00:00 8642.35 8789.00 8488.00 8736.03 \n",
"21 Wed 22 Jan, 2020 00:00:00 8736.04 8818.00 8590.00 8682.36 \n",
"22 Thu 23 Jan, 2020 00:00:00 8682.77 8691.81 8306.39 8404.52 \n",
"23 Fri 24 Jan, 2020 00:00:00 8404.52 8528.02 8238.00 8439.00 \n",
"24 Sat 25 Jan, 2020 00:00:00 8438.99 8451.26 8254.90 8340.58 \n",
"25 Sun 26 Jan, 2020 00:00:00 8340.01 8618.13 8293.66 8615.00 \n",
"26 Mon 27 Jan, 2020 00:00:00 8614.39 9000.00 8535.00 8907.57 \n",
"27 Tue 28 Jan, 2020 00:00:00 8907.57 9400.00 8862.40 9374.21 \n",
"28 Wed 29 Jan, 2020 00:00:00 9375.34 9449.24 9216.00 9301.53 \n",
"29 Thu 30 Jan, 2020 00:00:00 9301.57 9578.00 9204.44 9513.21 \n",
"30 Fri 31 Jan, 2020 00:00:00 9511.52 9530.22 9210.01 9352.89 \n",
"31 Sat 01 Feb, 2020 00:00:00 9351.71 9464.53 9281.00 9384.61 \n",
"\n",
" CloseTime \n",
"0 Wed 01 Jan, 2020 23:59:59 \n",
"1 Thu 02 Jan, 2020 23:59:59 \n",
"2 Fri 03 Jan, 2020 23:59:59 \n",
"3 Sat 04 Jan, 2020 23:59:59 \n",
"4 Sun 05 Jan, 2020 23:59:59 \n",
"5 Mon 06 Jan, 2020 23:59:59 \n",
"6 Tue 07 Jan, 2020 23:59:59 \n",
"7 Wed 08 Jan, 2020 23:59:59 \n",
"8 Thu 09 Jan, 2020 23:59:59 \n",
"9 Fri 10 Jan, 2020 23:59:59 \n",
"10 Sat 11 Jan, 2020 23:59:59 \n",
"11 Sun 12 Jan, 2020 23:59:59 \n",
"12 Mon 13 Jan, 2020 23:59:59 \n",
"13 Tue 14 Jan, 2020 23:59:59 \n",
"14 Wed 15 Jan, 2020 23:59:59 \n",
"15 Thu 16 Jan, 2020 23:59:59 \n",
"16 Fri 17 Jan, 2020 23:59:59 \n",
"17 Sat 18 Jan, 2020 23:59:59 \n",
"18 Sun 19 Jan, 2020 23:59:59 \n",
"19 Mon 20 Jan, 2020 23:59:59 \n",
"20 Tue 21 Jan, 2020 23:59:59 \n",
"21 Wed 22 Jan, 2020 23:59:59 \n",
"22 Thu 23 Jan, 2020 23:59:59 \n",
"23 Fri 24 Jan, 2020 23:59:59 \n",
"24 Sat 25 Jan, 2020 23:59:59 \n",
"25 Sun 26 Jan, 2020 23:59:59 \n",
"26 Mon 27 Jan, 2020 23:59:59 \n",
"27 Tue 28 Jan, 2020 23:59:59 \n",
"28 Wed 29 Jan, 2020 23:59:59 \n",
"29 Thu 30 Jan, 2020 23:59:59 \n",
"30 Fri 31 Jan, 2020 23:59:59 \n",
"31 Sat 01 Feb, 2020 23:59:59 "
],
"text/html": [
"\n",
" <div id=\"df-3eb2f382-5b3e-4370-9798-4b6bb4034722\">\n",
" <div class=\"colab-df-container\">\n",
" <div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>OpenTime</th>\n",
" <th>Open</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
" <th>Close</th>\n",
" <th>CloseTime</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Wed 01 Jan, 2020 00:00:00</td>\n",
" <td>7195.24</td>\n",
" <td>7255.00</td>\n",
" <td>7175.15</td>\n",
" <td>7200.85</td>\n",
" <td>Wed 01 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Thu 02 Jan, 2020 00:00:00</td>\n",
" <td>7200.77</td>\n",
" <td>7212.50</td>\n",
" <td>6924.74</td>\n",
" <td>6965.71</td>\n",
" <td>Thu 02 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Fri 03 Jan, 2020 00:00:00</td>\n",
" <td>6965.49</td>\n",
" <td>7405.00</td>\n",
" <td>6871.04</td>\n",
" <td>7344.96</td>\n",
" <td>Fri 03 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Sat 04 Jan, 2020 00:00:00</td>\n",
" <td>7345.00</td>\n",
" <td>7404.00</td>\n",
" <td>7272.21</td>\n",
" <td>7354.11</td>\n",
" <td>Sat 04 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Sun 05 Jan, 2020 00:00:00</td>\n",
" <td>7354.19</td>\n",
" <td>7495.00</td>\n",
" <td>7318.00</td>\n",
" <td>7358.75</td>\n",
" <td>Sun 05 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Mon 06 Jan, 2020 00:00:00</td>\n",
" <td>7357.64</td>\n",
" <td>7795.34</td>\n",
" <td>7346.76</td>\n",
" <td>7758.00</td>\n",
" <td>Mon 06 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Tue 07 Jan, 2020 00:00:00</td>\n",
" <td>7758.90</td>\n",
" <td>8207.68</td>\n",
" <td>7723.71</td>\n",
" <td>8145.28</td>\n",
" <td>Tue 07 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>Wed 08 Jan, 2020 00:00:00</td>\n",
" <td>8145.92</td>\n",
" <td>8455.00</td>\n",
" <td>7870.00</td>\n",
" <td>8055.98</td>\n",
" <td>Wed 08 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Thu 09 Jan, 2020 00:00:00</td>\n",
" <td>8054.72</td>\n",
" <td>8055.96</td>\n",
" <td>7750.00</td>\n",
" <td>7817.76</td>\n",
" <td>Thu 09 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Fri 10 Jan, 2020 00:00:00</td>\n",
" <td>7817.74</td>\n",
" <td>8199.00</td>\n",
" <td>7672.00</td>\n",
" <td>8197.02</td>\n",
" <td>Fri 10 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Sat 11 Jan, 2020 00:00:00</td>\n",
" <td>8198.86</td>\n",
" <td>8286.34</td>\n",
" <td>8003.16</td>\n",
" <td>8020.01</td>\n",
" <td>Sat 11 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Sun 12 Jan, 2020 00:00:00</td>\n",
" <td>8020.01</td>\n",
" <td>8197.00</td>\n",
" <td>7960.00</td>\n",
" <td>8184.98</td>\n",
" <td>Sun 12 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Mon 13 Jan, 2020 00:00:00</td>\n",
" <td>8184.97</td>\n",
" <td>8196.00</td>\n",
" <td>8055.89</td>\n",
" <td>8110.34</td>\n",
" <td>Mon 13 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Tue 14 Jan, 2020 00:00:00</td>\n",
" <td>8110.34</td>\n",
" <td>8880.00</td>\n",
" <td>8105.54</td>\n",
" <td>8810.01</td>\n",
" <td>Tue 14 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>Wed 15 Jan, 2020 00:00:00</td>\n",
" <td>8814.64</td>\n",
" <td>8916.48</td>\n",
" <td>8564.00</td>\n",
" <td>8821.41</td>\n",
" <td>Wed 15 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Thu 16 Jan, 2020 00:00:00</td>\n",
" <td>8820.01</td>\n",
" <td>8859.81</td>\n",
" <td>8586.00</td>\n",
" <td>8720.01</td>\n",
" <td>Thu 16 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>Fri 17 Jan, 2020 00:00:00</td>\n",
" <td>8720.15</td>\n",
" <td>9041.65</td>\n",
" <td>8672.44</td>\n",
" <td>8913.28</td>\n",
" <td>Fri 17 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>Sat 18 Jan, 2020 00:00:00</td>\n",
" <td>8913.27</td>\n",
" <td>8988.88</td>\n",
" <td>8806.38</td>\n",
" <td>8915.96</td>\n",
" <td>Sat 18 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>Sun 19 Jan, 2020 00:00:00</td>\n",
" <td>8915.09</td>\n",
" <td>9198.98</td>\n",
" <td>8466.00</td>\n",
" <td>8701.70</td>\n",
" <td>Sun 19 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>Mon 20 Jan, 2020 00:00:00</td>\n",
" <td>8701.72</td>\n",
" <td>8746.99</td>\n",
" <td>8521.28</td>\n",
" <td>8642.35</td>\n",
" <td>Mon 20 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>Tue 21 Jan, 2020 00:00:00</td>\n",
" <td>8642.35</td>\n",
" <td>8789.00</td>\n",
" <td>8488.00</td>\n",
" <td>8736.03</td>\n",
" <td>Tue 21 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>Wed 22 Jan, 2020 00:00:00</td>\n",
" <td>8736.04</td>\n",
" <td>8818.00</td>\n",
" <td>8590.00</td>\n",
" <td>8682.36</td>\n",
" <td>Wed 22 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>Thu 23 Jan, 2020 00:00:00</td>\n",
" <td>8682.77</td>\n",
" <td>8691.81</td>\n",
" <td>8306.39</td>\n",
" <td>8404.52</td>\n",
" <td>Thu 23 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>Fri 24 Jan, 2020 00:00:00</td>\n",
" <td>8404.52</td>\n",
" <td>8528.02</td>\n",
" <td>8238.00</td>\n",
" <td>8439.00</td>\n",
" <td>Fri 24 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>Sat 25 Jan, 2020 00:00:00</td>\n",
" <td>8438.99</td>\n",
" <td>8451.26</td>\n",
" <td>8254.90</td>\n",
" <td>8340.58</td>\n",
" <td>Sat 25 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>Sun 26 Jan, 2020 00:00:00</td>\n",
" <td>8340.01</td>\n",
" <td>8618.13</td>\n",
" <td>8293.66</td>\n",
" <td>8615.00</td>\n",
" <td>Sun 26 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>Mon 27 Jan, 2020 00:00:00</td>\n",
" <td>8614.39</td>\n",
" <td>9000.00</td>\n",
" <td>8535.00</td>\n",
" <td>8907.57</td>\n",
" <td>Mon 27 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>Tue 28 Jan, 2020 00:00:00</td>\n",
" <td>8907.57</td>\n",
" <td>9400.00</td>\n",
" <td>8862.40</td>\n",
" <td>9374.21</td>\n",
" <td>Tue 28 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>Wed 29 Jan, 2020 00:00:00</td>\n",
" <td>9375.34</td>\n",
" <td>9449.24</td>\n",
" <td>9216.00</td>\n",
" <td>9301.53</td>\n",
" <td>Wed 29 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>Thu 30 Jan, 2020 00:00:00</td>\n",
" <td>9301.57</td>\n",
" <td>9578.00</td>\n",
" <td>9204.44</td>\n",
" <td>9513.21</td>\n",
" <td>Thu 30 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>Fri 31 Jan, 2020 00:00:00</td>\n",
" <td>9511.52</td>\n",
" <td>9530.22</td>\n",
" <td>9210.01</td>\n",
" <td>9352.89</td>\n",
" <td>Fri 31 Jan, 2020 23:59:59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>Sat 01 Feb, 2020 00:00:00</td>\n",
" <td>9351.71</td>\n",
" <td>9464.53</td>\n",
" <td>9281.00</td>\n",
" <td>9384.61</td>\n",
" <td>Sat 01 Feb, 2020 23:59:59</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
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]
},
"metadata": {},
"execution_count": 7
}
],
"source": [
"data_df = pd.DataFrame(data,columns = [\"OpenTime\", \"Open\", \"High\", \"Low\", \"Close\",f\"{base} Volume\",\"CloseTime\",f\"{quote} Volume\",\"No. of trades\", f\"Taker Buy ({base})\", f\"Taker Buy ({quote})\", \"Ignore\"]).iloc[:, :5]\n",
"data_df['OpenTime'] = open_times\n",
"data_df['CloseTime'] = close_times\n",
"\n",
"data_df.iloc[:, 1:5] = data_df.iloc[:, 1:5].astype(float).round(decimals=2)\n",
"\n",
"data_df"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.4"
},
"colab": {
"name": "historical_klines.ipynb",
"provenance": [],
"collapsed_sections": [],
"include_colab_link": true
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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