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股票数据分析

刘早起@微信公众号:早起Python

股票数据分析

在线刷题

检查 or 强化 Pandas 数据分析操作？👉在线体验「Pandas进阶修炼300题」

Note

本页面代码可以在线编辑、执行！

本页面数据说明

为了更好的介绍相关操作，本页面使用 某股票数据 数据进行展开，你应该对数据字段、数值、类型等相关信息做一个大致了解！

import pandas as pd
import warnings
warnings.filterwarnings("ignore")
df1 = pd.read_csv("000001_daily.csv")
df2 = pd.read_csv("000001_5min.csv")
df1.head()
日期 开盘 收盘 最高 最低 成交量 成交额 振幅 涨跌幅 涨跌额 换手率
0 2017/1/3 8.27 8.32 8.34 8.25 459840 420595184 1.09 0.73 0.06 0.31
1 2017/1/4 8.31 8.32 8.34 8.30 449330 411503440 0.48 0.00 0.00 0.31
2 2017/1/5 8.33 8.33 8.34 8.31 344373 315769696 0.36 0.12 0.01 0.24
3 2017/1/6 8.33 8.29 8.33 8.27 358154 327176432 0.72 -0.48 -0.04 0.24
4 2017/1/9 8.29 8.31 8.33 8.27 361082 329994608 0.72 0.24 0.02 0.21

时间类型转换

将 df1 和 df2 的 日期 列转换为 pandas 支持的时间格式

df1['日期'] = pd.to_datetime(df1['日期'])
df2['时间'] = pd.to_datetime(df2['时间'])
# df1['日期'] = df1['日期'].astype('datetime64[ns]')

日期筛选

按区间筛选

筛选出 df2 时间在 2021-08-03 09:35:00 与 2021-08-04 15:00:00 之间的数据

df2[(df2['时间'] > '2021-08-03 09:35:00') & (df2['时间'] < '2021-08-04 15:00:00')]
时间 开盘 收盘 最高 最低 涨跌幅 涨跌额 成交量 成交额 振幅 换手率
1 2021-08-03 09:40:00 17.77 17.76 17.83 17.66 -0.11 -0.02 41508 73683531 0.96 0.02
2 2021-08-03 09:45:00 17.77 17.77 17.83 17.73 0.06 0.01 18521 32915794 0.56 0.01
3 2021-08-03 09:50:00 17.77 17.72 17.78 17.70 -0.28 -0.05 24424 43323693 0.45 0.01
4 2021-08-03 09:55:00 17.71 17.77 17.78 17.70 0.28 0.05 23197 41110937 0.45 0.01
5 2021-08-03 10:00:00 17.78 17.81 17.83 17.74 0.23 0.04 18111 32208076 0.51 0.01
... ... ... ... ... ... ... ... ... ... ... ...
90 2021-08-04 14:35:00 17.81 17.81 17.83 17.78 0.00 0.00 12903 22973276 0.28 0.01
91 2021-08-04 14:40:00 17.82 17.80 17.85 17.79 -0.06 -0.01 12254 21835743 0.34 0.01
92 2021-08-04 14:45:00 17.82 17.82 17.84 17.80 0.11 0.02 9893 17631076 0.22 0.01
93 2021-08-04 14:50:00 17.81 17.80 17.83 17.80 -0.11 -0.02 12127 21603534 0.17 0.01
94 2021-08-04 14:55:00 17.80 17.81 17.84 17.79 0.06 0.01 17028 30332096 0.28 0.01

94 rows × 11 columns

按指定时间筛选

筛选 df2 时间为 2021-08-03 的全部数据

df2.set_index('时间').truncate(after=pd.Timestamp('2021-08-04'))
开盘 收盘 最高 最低 涨跌幅 涨跌额 成交量 成交额 振幅 换手率
时间
2021-08-03 09:35:00 17.99 17.78 18.02 17.75 -1.28 -0.23 52807 94339287 1.50 0.03
2021-08-03 09:40:00 17.77 17.76 17.83 17.66 -0.11 -0.02 41508 73683531 0.96 0.02
2021-08-03 09:45:00 17.77 17.77 17.83 17.73 0.06 0.01 18521 32915794 0.56 0.01
2021-08-03 09:50:00 17.77 17.72 17.78 17.70 -0.28 -0.05 24424 43323693 0.45 0.01
2021-08-03 09:55:00 17.71 17.77 17.78 17.70 0.28 0.05 23197 41110937 0.45 0.01
2021-08-03 10:00:00 17.78 17.81 17.83 17.74 0.23 0.04 18111 32208076 0.51 0.01
2021-08-03 10:05:00 17.83 17.84 17.91 17.79 0.17 0.03 28273 50498772 0.67 0.01
2021-08-03 10:10:00 17.84 18.01 18.01 17.83 0.95 0.17 37675 67585497 1.01 0.02
2021-08-03 10:15:00 18.01 18.05 18.09 18.01 0.22 0.04 31315 56528108 0.44 0.02
2021-08-03 10:20:00 18.04 18.00 18.07 17.98 -0.28 -0.05 25998 46873326 0.50 0.01
2021-08-03 10:25:00 18.01 17.99 18.03 17.98 -0.06 -0.01 19840 35724912 0.28 0.01
2021-08-03 10:30:00 17.99 17.89 18.00 17.89 -0.56 -0.10 22437 40295707 0.61 0.01
2021-08-03 10:35:00 17.89 17.96 17.97 17.89 0.39 0.07 16344 29302241 0.45 0.01
2021-08-03 10:40:00 17.97 17.94 17.98 17.94 -0.11 -0.02 13929 25017058 0.22 0.01
2021-08-03 10:45:00 17.94 17.99 18.04 17.90 0.28 0.05 20556 36934160 0.78 0.01
2021-08-03 10:50:00 18.00 18.11 18.11 17.99 0.67 0.12 24688 44603411 0.67 0.01
2021-08-03 10:55:00 18.11 18.01 18.15 18.01 -0.55 -0.10 23020 41643532 0.77 0.01
2021-08-03 11:00:00 18.01 18.03 18.05 17.99 0.11 0.02 12102 21795475 0.33 0.01
2021-08-03 11:05:00 18.04 18.03 18.05 18.00 0.00 0.00 17303 31197226 0.28 0.01
2021-08-03 11:10:00 18.03 18.02 18.04 18.00 -0.06 -0.01 12736 22940014 0.22 0.01
2021-08-03 11:15:00 18.03 18.00 18.03 18.00 -0.11 -0.02 12273 22104969 0.17 0.01
2021-08-03 11:20:00 18.02 18.07 18.10 18.01 0.39 0.07 20951 37844518 0.50 0.01
2021-08-03 11:25:00 18.08 18.02 18.09 18.01 -0.28 -0.05 15905 28711245 0.44 0.01
2021-08-03 11:30:00 18.02 18.02 18.05 18.00 0.00 0.00 13814 24893817 0.28 0.01
2021-08-03 13:05:00 18.02 18.01 18.04 18.00 -0.06 -0.01 16530 29783440 0.22 0.01
2021-08-03 13:10:00 18.01 18.04 18.07 18.01 0.17 0.03 14666 26464258 0.33 0.01
2021-08-03 13:15:00 18.04 17.99 18.05 17.99 -0.28 -0.05 13880 25011176 0.33 0.01
2021-08-03 13:20:00 17.99 17.98 18.02 17.98 -0.06 -0.01 13451 24208140 0.22 0.01
2021-08-03 13:25:00 17.98 18.00 18.01 17.97 0.11 0.02 14024 25229291 0.22 0.01
2021-08-03 13:30:00 18.00 18.01 18.05 17.99 0.06 0.01 15333 27633217 0.33 0.01
2021-08-03 13:35:00 18.01 18.00 18.03 17.98 -0.06 -0.01 16424 29582866 0.28 0.01
2021-08-03 13:40:00 18.00 17.99 18.02 17.98 -0.06 -0.01 14696 26452384 0.22 0.01
2021-08-03 13:45:00 18.00 17.99 18.02 17.98 0.00 0.00 14632 26334531 0.22 0.01
2021-08-03 13:50:00 18.01 17.99 18.01 17.98 0.00 0.00 11746 21134264 0.17 0.01
2021-08-03 13:55:00 17.98 17.94 18.00 17.92 -0.28 -0.05 17023 30591848 0.44 0.01
2021-08-03 14:00:00 17.93 17.95 17.96 17.93 0.06 0.01 8906 15983206 0.17 0.00
2021-08-03 14:05:00 17.95 17.94 17.96 17.93 -0.06 -0.01 9690 17392582 0.17 0.00
2021-08-03 14:10:00 17.95 17.93 17.96 17.93 -0.06 -0.01 10427 18707878 0.17 0.01
2021-08-03 14:15:00 17.93 17.92 17.96 17.92 -0.06 -0.01 10498 18828673 0.22 0.01
2021-08-03 14:20:00 17.93 17.92 17.94 17.91 0.00 0.00 16589 29733764 0.17 0.01
2021-08-03 14:25:00 17.91 17.93 17.94 17.90 0.06 0.01 17581 31496394 0.22 0.01
2021-08-03 14:30:00 17.92 17.94 17.96 17.91 0.06 0.01 12845 23035897 0.28 0.01
2021-08-03 14:35:00 17.94 17.93 17.94 17.90 -0.06 -0.01 14611 26183179 0.22 0.01
2021-08-03 14:40:00 17.93 17.93 17.94 17.90 0.00 0.00 12076 21636917 0.22 0.01
2021-08-03 14:45:00 17.90 17.93 17.93 17.89 0.00 0.00 16397 29359350 0.22 0.01
2021-08-03 14:50:00 17.93 17.97 17.98 17.91 0.22 0.04 19476 34965331 0.39 0.01
2021-08-03 14:55:00 17.96 17.93 17.97 17.91 -0.22 -0.04 17597 31563908 0.33 0.01
2021-08-03 15:00:00 17.92 17.89 17.94 17.89 -0.22 -0.04 20126 36034747 0.28 0.01

金融计算

涨跌额

df1 新增一列 涨跌，计算前后两日收盘价之差

注意：虽然我们的df1包含涨跌额列，但是这个操作很常用，所以练习一下

df1['涨跌']  = df1.收盘.diff()

涨跌幅

df1 新增一列 涨跌变化率，计算前后两日收盘价之差的变化率

注意：虽然我们的df1包含涨跌幅列，但是这个操作很常用，所以练习一下，结果可以用于验证

df1['涨跌变化率'] = (df1.收盘.pct_change()).apply(lambda x: format(x, '.2%'))

移动均值

计算收盘价的5日移动均线

df1.收盘.rolling(window=5).mean()

0          NaN
1          NaN
2          NaN
3          NaN
4        8.314
         ...  
1141    18.672
1142    18.792
1143    19.298
1144    19.650
1145    19.676
Name: 收盘, Length: 1146, dtype: float64

移动均值（可视化）

计算并绘制收盘价的5日移动均线

df1.收盘.rolling(window=5).mean().plot()

<AxesSubplot:>
../../_images/股票数据分析_18_1.png

移动均值（可视化）

同时计算并绘制 df1 的收盘价、5日均线、20日均线

df1.set_index("日期")['收盘'].plot()
df1.set_index("日期")['收盘'].rolling(5).mean().plot()
df1.set_index("日期")['收盘'].rolling(20).mean().plot()

<AxesSubplot:xlabel='日期'>
../../_images/股票数据分析_20_1.png

指数移动平均值（EMA）

根据 df1 计算 EMA20

df1['EMA20'] = df1['收盘'].ewm(span=20,min_periods=0,adjust=False,ignore_na=False).mean()

MACD

计算 df1 的 MACD 指标

exp1 = df1['收盘'].ewm(span=12, adjust=False).mean()
exp2 = df1['收盘'].ewm(span=26, adjust=False).mean()
df1['MACD'] = exp1 - exp2
df1['Signal line'] = df1['MACD'].ewm(span=9, adjust=False).mean()

布林指标

计算并绘制布林指标，计算方法参考百度百科

df1['former 30 days rolling Close mean'] = df1['收盘'].rolling(20).mean()
df1['upper bound'] = df1['former 30 days rolling Close mean'] + \
    2*df1['收盘'].rolling(20).std()  # 在这里我们取20天内的标准差
df1['lower bound'] = df1['former 30 days rolling Close mean'] - \
    2*df1['收盘'].rolling(20).std()

import matplotlib.pyplot as plt

plt.rcParams['font.sans-serif'] = ['Songti SC'] #设置中文，如果本句代码导致失效，可以点击https://mp.weixin.qq.com/s/WKOGvQP-6QUAP00ZXjhweg

df1.set_index("日期")[['收盘', 'former 30 days rolling Close mean','upper bound','lower bound' ]].plot(figsize=(16, 6))

plt.show()
../../_images/股票数据分析_26_0.png

日期移动

移动值

将 df1 的索引设置为日期，将 df1 数据向后移动一天

df1.set_index('日期').shift(1)
开盘 收盘 最高 最低 成交量 成交额 振幅 涨跌幅 涨跌额 换手率 涨跌 涨跌变化率 EMA20 MACD Signal line former 30 days rolling Close mean upper bound lower bound
日期
2017-01-03 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2017-01-04 8.27 8.32 8.34 8.25 459840.0 4.205952e+08 1.09 0.73 0.06 0.31 NaN nan% 8.320000 0.000000 0.000000 NaN NaN NaN
2017-01-05 8.31 8.32 8.34 8.30 449330.0 4.115034e+08 0.48 0.00 0.00 0.31 0.00 0.00% 8.320000 0.000000 0.000000 NaN NaN NaN
2017-01-06 8.33 8.33 8.34 8.31 344373.0 3.157697e+08 0.36 0.12 0.01 0.24 0.01 0.12% 8.320952 0.000798 0.000160 NaN NaN NaN
2017-01-09 8.33 8.29 8.33 8.27 358154.0 3.271764e+08 0.72 -0.48 -0.04 0.24 -0.04 -0.48% 8.318005 -0.001777 -0.000228 NaN NaN NaN
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
2021-09-08 18.60 19.24 19.56 18.35 1622344.0 3.067366e+09 6.56 4.28 0.79 0.84 0.79 4.28% 18.816960 -0.369698 -0.414708 19.0895 20.861284 17.317716
2021-09-09 19.24 19.23 19.55 19.10 1026201.0 1.979771e+09 2.34 -0.05 -0.01 0.53 -0.01 -0.05% 18.856297 -0.293684 -0.390503 19.0605 20.801346 17.319654
2021-09-10 19.11 19.00 19.15 18.80 739506.0 1.399536e+09 1.82 -1.20 -0.23 0.38 -0.23 -1.20% 18.869983 -0.249129 -0.362229 19.0160 20.712503 17.319497
2021-09-13 18.89 20.57 20.77 18.84 2314945.0 4.668362e+09 10.16 8.26 1.57 1.19 1.57 8.26% 19.031889 -0.086141 -0.307011 19.0500 20.844670 17.255330
2021-09-14 20.36 20.21 20.51 19.81 1297228.0 2.606152e+09 3.40 -1.75 -0.36 0.67 -0.36 -1.75% 19.144090 0.013821 -0.242845 19.0630 20.888620 17.237380

1146 rows × 18 columns

移动索引

将 df1 的索引设置为日期，并将全部日期向后移动一天

import datetime
df1.set_index('日期').shift(freq=datetime.timedelta(1))
开盘 收盘 最高 最低 成交量 成交额 振幅 涨跌幅 涨跌额 换手率 涨跌 涨跌变化率 EMA20 MACD Signal line former 30 days rolling Close mean upper bound lower bound
日期
2017-01-04 8.27 8.32 8.34 8.25 459840 420595184 1.09 0.73 0.06 0.31 NaN nan% 8.320000 0.000000 0.000000 NaN NaN NaN
2017-01-05 8.31 8.32 8.34 8.30 449330 411503440 0.48 0.00 0.00 0.31 0.00 0.00% 8.320000 0.000000 0.000000 NaN NaN NaN
2017-01-06 8.33 8.33 8.34 8.31 344373 315769696 0.36 0.12 0.01 0.24 0.01 0.12% 8.320952 0.000798 0.000160 NaN NaN NaN
2017-01-07 8.33 8.29 8.33 8.27 358154 327176432 0.72 -0.48 -0.04 0.24 -0.04 -0.48% 8.318005 -0.001777 -0.000228 NaN NaN NaN
2017-01-10 8.29 8.31 8.33 8.27 361082 329994608 0.72 0.24 0.02 0.21 0.02 0.24% 8.317242 -0.002179 -0.000618 NaN NaN NaN
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
2021-09-09 19.24 19.23 19.55 19.10 1026201 1979771472 2.34 -0.05 -0.01 0.53 -0.01 -0.05% 18.856297 -0.293684 -0.390503 19.0605 20.801346 17.319654
2021-09-10 19.11 19.00 19.15 18.80 739506 1399536016 1.82 -1.20 -0.23 0.38 -0.23 -1.20% 18.869983 -0.249129 -0.362229 19.0160 20.712503 17.319497
2021-09-11 18.89 20.57 20.77 18.84 2314945 4668361728 10.16 8.26 1.57 1.19 1.57 8.26% 19.031889 -0.086141 -0.307011 19.0500 20.844670 17.255330
2021-09-14 20.36 20.21 20.51 19.81 1297228 2606152384 3.40 -1.75 -0.36 0.67 -0.36 -1.75% 19.144090 0.013821 -0.242845 19.0630 20.888620 17.237380
2021-09-15 20.18 19.37 20.27 19.27 1158173 2272080160 4.95 -4.16 -0.84 0.60 -0.84 -4.16% 19.165606 0.024972 -0.189281 19.0480 20.857479 17.238521

1146 rows × 18 columns

日期重采样

日 -> 周

按周对 df1 进行重采样，保留每周最后一个数据

df1.set_index('日期').resample('W').last()
开盘 收盘 最高 最低 成交量 成交额 振幅 涨跌幅 涨跌额 换手率 涨跌 涨跌变化率 EMA20 MACD Signal line former 30 days rolling Close mean upper bound lower bound
日期
2017-01-08 8.33 8.29 8.33 8.27 358154.0 3.271764e+08 0.72 -0.48 -0.04 0.24 -0.04 -0.48% 8.318005 -0.001777 -0.000228 NaN NaN NaN
2017-01-15 8.30 8.32 8.35 8.28 434301.0 3.976019e+08 0.84 0.12 0.01 0.26 0.01 0.12% 8.315026 -0.002529 -0.002001 NaN NaN NaN
2017-01-22 8.33 8.38 8.39 8.33 393329.0 3.618652e+08 0.72 0.48 0.04 0.23 0.04 0.48% 8.323220 0.005576 -0.000237 NaN NaN NaN
2017-01-29 8.43 8.49 8.50 8.42 420713.0 3.918443e+08 0.95 0.83 0.07 0.25 0.07 0.83% 8.359773 0.029337 0.012089 NaN NaN NaN
2017-02-05 8.50 8.42 8.52 8.39 315472.0 2.926179e+08 1.53 -0.82 -0.07 0.19 -0.07 -0.82% 8.365509 0.030296 0.015730 NaN NaN NaN
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
2021-08-22 19.97 19.42 20.07 18.70 1614628.0 3.119153e+09 6.74 -4.52 -0.92 0.83 -0.92 -4.52% 19.631205 -0.142627 -0.419982 18.8795 20.984246 16.774754
2021-08-29 18.56 18.39 18.88 18.31 728820.0 1.354409e+09 3.09 -0.38 -0.07 0.38 -0.07 -0.38% 19.335072 -0.307851 -0.292708 19.1150 20.952578 17.277422
2021-09-05 18.50 18.04 18.50 17.70 1394819.0 2.523273e+09 4.35 -1.96 -0.36 0.72 -0.36 -1.96% 18.806369 -0.493470 -0.416861 19.1445 20.911466 17.377534
2021-09-12 18.89 20.57 20.77 18.84 2314945.0 4.668362e+09 10.16 8.26 1.57 1.19 1.57 8.26% 19.031889 -0.086141 -0.307011 19.0500 20.844670 17.255330
2021-09-19 20.18 19.37 20.27 19.27 1158173.0 2.272080e+09 4.95 -4.16 -0.84 0.60 -0.84 -4.16% 19.165606 0.024972 -0.189281 19.0480 20.857479 17.238521

246 rows × 18 columns

日 -> 月

按月对 df1 进行重采样，保留每月最后一个数据

df1.set_index('日期').resample('M').last()
开盘 收盘 最高 最低 成交量 成交额 振幅 涨跌幅 涨跌额 换手率 涨跌 涨跌变化率 EMA20 MACD Signal line former 30 days rolling Close mean upper bound lower bound
日期
2017-01-31 8.43 8.49 8.50 8.42 420713 391844288 0.95 0.83 0.07 0.25 0.07 0.83% 8.359773 0.029337 0.012089 NaN NaN NaN
2017-02-28 8.59 8.64 8.67 8.58 369720 350366896 1.05 0.58 0.05 0.22 0.05 0.58% 8.573112 0.074404 0.075472 8.5665 8.773460 8.359540
2017-03-31 8.24 8.33 8.34 8.24 633121 578579040 1.21 1.09 0.09 0.37 0.09 1.09% 8.413994 -0.073842 -0.049755 8.4575 8.748768 8.166232
2017-04-30 8.12 8.15 8.15 8.08 286446 256106698 0.86 0.25 0.02 0.17 0.02 0.25% 8.218865 -0.078102 -0.079294 8.2270 8.428896 8.025104
2017-05-31 8.26 8.36 8.39 8.22 1033211 948741888 2.06 1.21 0.10 0.61 0.10 1.21% 8.056467 0.011297 -0.052053 7.9735 8.314907 7.632093
2017-06-30 8.56 8.55 8.59 8.47 499633 468003520 1.40 -0.47 -0.04 0.30 -0.04 -0.47% 8.368898 0.107020 0.081328 8.3430 8.612198 8.073802
2017-07-31 10.12 9.99 10.14 9.77 1575864 1671814032 3.68 -0.70 -0.07 0.93 -0.07 -0.70% 9.708929 0.401497 0.434813 9.6690 11.022139 8.315861
2017-08-31 10.71 10.60 10.76 10.47 1151786 1297730592 2.70 -1.40 -0.15 0.68 -0.15 -1.40% 10.224083 0.250813 0.182339 10.1250 11.030480 9.219520
2017-09-30 10.24 10.43 10.48 10.18 682280 753852528 2.94 2.25 0.23 0.40 0.23 2.25% 10.512902 0.007831 0.083505 10.6590 11.128575 10.189425
2017-10-31 10.87 10.86 10.90 10.71 627491 721237472 1.75 -0.18 -0.02 0.37 -0.02 -0.18% 10.726516 0.061093 0.063177 10.7060 11.164666 10.247334
2017-11-30 13.02 12.70 13.05 12.58 1379636 1866700880 3.58 -3.35 -0.44 0.82 -0.44 -3.35% 12.629801 0.596790 0.642198 12.5160 14.678459 10.353541
2017-12-31 12.53 12.62 12.75 12.42 982916 1303222048 2.63 0.72 0.09 0.58 0.09 0.72% 12.577670 0.089316 0.108042 12.5215 13.033227 12.009773
2018-01-31 12.92 13.37 13.37 12.85 1747729 2423104768 4.01 3.08 0.40 1.03 0.40 3.08% 13.275908 0.181650 0.252009 13.2490 14.398387 12.099613
2018-02-28 11.42 11.37 11.51 11.25 1214146 1463313696 2.24 -1.98 -0.23 0.72 -0.23 -1.98% 12.166929 -0.425308 -0.337732 12.3780 14.314428 10.441572
2018-03-31 10.36 10.22 10.37 10.20 752174 823438176 1.64 -1.45 -0.15 0.44 -0.15 -1.45% 10.904021 -0.439439 -0.396420 10.9595 11.866792 10.052208
2018-04-30 10.81 10.17 10.83 9.95 2709796 2958464272 8.19 -5.31 -0.57 1.60 -0.57 -5.31% 10.724916 -0.081372 -0.109566 10.5930 11.340039 9.845961
2018-05-31 9.43 9.50 9.51 9.34 987360 999216336 1.81 1.06 0.10 0.58 0.10 1.06% 10.039416 -0.252155 -0.191171 10.0880 10.684502 9.491498
2018-06-30 8.33 8.41 8.45 8.28 675300 611346096 2.06 2.06 0.17 0.39 0.17 2.06% 9.096154 -0.391787 -0.315595 9.1725 10.036368 8.308632
2018-07-31 8.83 8.88 8.95 8.71 720151 674484656 2.71 0.34 0.03 0.42 0.03 0.34% 8.616982 0.004301 -0.105048 8.4140 9.097225 7.730775
2018-08-31 9.59 9.59 9.78 9.56 1310865 1337898864 2.30 0.10 0.01 0.76 0.01 0.10% 9.057319 0.287543 0.166752 8.8730 10.003665 7.742335
2018-09-30 10.24 10.51 10.73 10.24 2110243 2331358288 4.80 3.04 0.31 1.23 0.31 3.04% 9.710813 0.304713 0.231171 9.6705 10.401454 8.939546
2018-10-31 10.41 10.37 10.45 10.21 1152684 1252156768 2.32 0.10 0.01 0.67 0.01 0.10% 10.142958 0.229796 0.220981 10.1165 10.920288 9.312712
2018-11-30 9.68 9.82 9.82 9.63 594715 610571536 1.97 1.66 0.16 0.35 0.16 1.66% 9.948735 -0.093728 -0.044225 10.0100 10.464498 9.555502
2018-12-31 8.77 8.84 8.92 8.77 576604 541571008 1.72 1.14 0.10 0.34 0.10 1.14% 9.304771 -0.303912 -0.229095 9.4395 10.357747 8.521253
2019-01-31 10.44 10.56 10.66 10.40 831623 922602880 2.50 1.44 0.15 0.48 0.15 1.44% 9.937361 0.276734 0.178894 9.8290 10.712364 8.945636
2019-02-28 11.90 11.82 12.07 11.73 1113100 1383110816 2.87 -0.34 -0.04 0.65 -0.04 -0.34% 10.935832 0.482602 0.388196 10.8910 11.924581 9.857419
2019-03-31 11.72 12.28 12.28 11.67 1669506 2108295392 5.22 5.14 0.60 0.97 0.60 5.14% 11.849661 0.183377 0.260493 12.0355 12.653424 11.417576
2019-04-30 13.45 13.31 13.51 13.05 1116570 1542958576 3.39 -1.84 -0.25 0.65 -0.25 -1.84% 13.292738 0.336437 0.423715 13.4270 14.208041 12.645959
2019-05-31 11.62 11.64 11.86 11.57 686794 839375712 2.48 -0.34 -0.04 0.40 -0.04 -0.34% 12.069663 -0.265725 -0.246701 11.9550 12.445306 11.464694
2019-06-30 13.33 13.38 13.39 13.18 498094 682679968 1.58 0.53 0.07 0.29 0.07 0.53% 12.589743 0.313734 0.167801 12.3020 13.738188 10.865812
2019-07-31 13.90 13.73 13.92 13.68 634723 899227872 1.72 -1.72 -0.24 0.37 -0.24 -1.72% 13.504316 0.245858 0.241181 13.5060 14.024800 12.987200
2019-08-31 13.89 13.76 13.99 13.70 798501 1136119664 2.11 0.22 0.03 0.47 0.03 0.22% 13.955094 0.071912 0.170015 14.0210 15.087581 12.954419
2019-09-30 15.35 15.19 15.49 15.17 1046363 1645828528 2.06 -2.00 -0.31 0.54 -0.31 -2.00% 14.642265 0.347402 0.242229 14.4925 15.563945 13.421055
2019-10-31 16.02 15.86 16.07 15.84 862569 1407006432 1.43 -1.06 -0.17 0.44 -0.17 -1.06% 15.976129 0.339469 0.446000 16.1580 16.983963 15.332037
2019-11-30 15.14 14.89 15.15 14.78 653867 1001451104 2.45 -1.33 -0.20 0.34 -0.20 -1.33% 15.586805 -0.238369 -0.106934 15.8000 16.907829 14.692171
2019-12-31 16.17 16.05 16.23 15.91 704442 1154704352 1.98 -0.74 -0.12 0.36 -0.12 -0.74% 15.837680 0.168803 0.114792 15.6875 16.658314 14.716686
2020-01-31 15.52 15.14 15.52 14.99 1100592 1723394336 3.38 -3.51 -0.55 0.57 -0.55 -3.51% 15.975078 -0.075053 0.071022 16.1800 16.985377 15.374623
2020-02-29 14.45 14.10 14.64 14.06 1300644 1906892416 3.94 -4.15 -0.61 0.67 -0.61 -4.15% 14.789529 -0.222628 -0.237305 14.5100 15.312417 13.707583
2020-03-31 12.65 12.40 12.69 12.38 513370 662915472 2.47 -1.12 -0.14 0.26 -0.14 -1.12% 13.061722 -0.590896 -0.597096 13.2205 15.311931 11.129069
2020-04-30 13.62 13.53 13.92 13.48 819540 1155968240 3.23 -0.66 -0.09 0.42 -0.09 -0.66% 12.911223 0.079692 -0.091462 12.6885 13.519689 11.857311
2020-05-31 12.83 12.82 12.86 12.74 457808 594502128 0.93 -0.54 -0.07 0.24 -0.07 -0.54% 12.887432 -0.075630 -0.040344 13.0605 13.790503 12.330497
2020-06-30 12.65 12.62 12.70 12.54 937940 1199181600 1.27 0.00 0.00 0.48 0.00 0.00% 12.777390 -0.131097 -0.095965 12.9290 13.694847 12.163153
2020-07-31 13.10 13.16 13.35 13.07 1165822 1559068288 2.12 -0.23 -0.03 0.60 -0.03 -0.23% 13.676416 -0.104207 0.071230 14.1905 15.848876 12.532124
2020-08-31 15.12 14.90 15.50 14.81 1797130 2760350320 4.62 -0.33 -0.05 0.93 -0.05 -0.33% 14.329986 0.232792 0.195512 14.2745 15.226782 13.322218
2020-09-30 14.62 14.99 15.09 14.62 1217065 1838547600 3.21 2.53 0.37 0.63 0.37 2.53% 15.043294 0.120394 0.215259 15.1285 15.778885 14.478115
2020-10-31 17.56 17.57 18.18 17.42 1007804 1813064336 4.32 -0.11 -0.02 0.52 -0.02 -0.11% 16.799087 0.678363 0.637274 16.5465 18.837721 14.255279
2020-11-30 19.72 19.56 20.70 19.41 1581441 3213680464 6.61 0.20 0.04 0.81 0.04 0.20% 18.401708 0.681858 0.583008 18.2485 19.926711 16.570289
2020-12-31 19.03 19.16 19.40 18.84 924503 1781736288 2.94 0.74 0.14 0.48 0.14 0.74% 18.553552 0.104339 0.051644 18.5090 19.377584 17.640416
2021-01-31 22.63 22.91 23.36 22.53 1240258 2864101424 3.67 1.24 0.28 0.64 0.28 1.24% 21.340373 1.021672 0.905720 21.0670 24.103827 18.030173
2021-02-28 21.42 21.20 21.78 21.03 1124977 2424653760 3.42 -3.24 -0.71 0.58 -0.71 -3.24% 22.587741 0.209554 0.673290 23.1920 25.486934 20.897066
2021-03-31 21.59 21.83 21.89 21.42 777028 1699922176 2.16 0.37 0.08 0.40 0.08 0.37% 21.367022 -0.159452 -0.266009 21.2275 22.495700 19.959300
2021-04-30 23.17 23.11 23.31 22.83 561981 1308177200 2.05 -1.28 -0.30 0.29 -0.30 -1.28% 22.125681 0.502633 0.272419 21.7540 24.001248 19.506752
2021-05-31 24.33 24.20 24.53 23.91 515351 1244209040 2.53 -1.22 -0.30 0.27 -0.30 -1.22% 23.717712 0.590754 0.567379 23.7655 24.919267 22.611733
2021-06-30 22.36 22.62 22.93 22.35 403435 913285184 2.60 1.25 0.28 0.21 0.28 1.25% 23.181017 -0.243393 -0.122945 23.3965 24.896090 21.896910
2021-07-31 17.92 17.69 18.05 17.24 950156 1679747312 4.51 -1.50 -0.27 0.49 -0.27 -1.50% 20.075455 -1.246638 -0.945724 20.4435 23.662851 17.224149
2021-08-31 17.72 17.80 17.93 17.31 1174868 2072006848 3.50 0.45 0.08 0.61 0.08 0.45% 19.049708 -0.464633 -0.344565 19.0960 20.987014 17.204986
2021-09-30 20.18 19.37 20.27 19.27 1158173 2272080160 4.95 -4.16 -0.84 0.60 -0.84 -4.16% 19.165606 0.024972 -0.189281 19.0480 20.857479 17.238521

分钟 -> 日

按日对 df2 进行重采样，保留每天最后一个数据

df2.set_index('时间').resample('D').last()
开盘 收盘 最高 最低 涨跌幅 涨跌额 成交量 成交额 振幅 换手率
时间
2021-08-03 17.92 17.89 17.94 17.89 -0.22 -0.04 20126.0 36034747.0 0.28 0.01
2021-08-04 17.81 17.81 17.82 17.80 0.00 0.00 12422.0 22122442.0 0.11 0.01
2021-08-05 17.64 17.68 17.68 17.64 0.17 0.03 15602.0 27568733.0 0.23 0.01
2021-08-06 17.84 17.86 17.87 17.84 0.06 0.01 13251.0 23647402.0 0.17 0.01
2021-08-07 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2021-08-08 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2021-08-09 19.07 19.06 19.09 19.06 -0.16 -0.03 16831.0 32092450.0 0.16 0.01
2021-08-10 19.72 19.73 19.74 19.70 0.05 0.01 14968.0 29523092.0 0.20 0.01
2021-08-11 19.74 19.81 19.81 19.74 0.35 0.07 17181.0 34015140.0 0.35 0.01
2021-08-12 19.89 19.89 19.89 19.87 0.00 0.00 7066.0 14051666.0 0.10 0.00
2021-08-13 19.87 19.89 19.89 19.85 0.20 0.04 11754.0 23367450.0 0.20 0.01
2021-08-14 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2021-08-15 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2021-08-16 19.91 19.95 19.95 19.89 0.20 0.04 8498.0 16936079.0 0.30 0.00
2021-08-17 19.69 19.67 19.70 19.66 -0.15 -0.03 7809.0 15366451.0 0.20 0.00
2021-08-18 20.66 20.62 20.69 20.62 -0.24 -0.05 25252.0 52116616.0 0.34 0.01
2021-08-19 20.32 20.34 20.34 20.31 0.15 0.03 13753.0 27959791.0 0.15 0.01
2021-08-20 19.43 19.42 19.43 19.39 0.00 0.00 24246.0 47066098.0 0.21 0.01
2021-08-21 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2021-08-22 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2021-08-23 19.28 19.30 19.30 19.28 0.16 0.03 10652.0 20550733.0 0.10 0.01
2021-08-24 19.35 19.36 19.40 19.34 0.10 0.02 15313.0 29654613.0 0.31 0.01
2021-08-25 19.13 19.16 19.16 19.12 0.16 0.03 13365.0 25584226.0 0.21 0.01
2021-08-26 18.49 18.46 18.50 18.46 -0.16 -0.03 19175.0 35413342.0 0.22 0.01
2021-08-27 18.37 18.39 18.39 18.33 0.05 0.01 17200.0 31599250.0 0.33 0.01
2021-08-28 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2021-08-29 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2021-08-30 17.70 17.72 17.72 17.68 0.11 0.02 21632.0 38313644.0 0.23 0.01
2021-08-31 17.79 17.80 17.81 17.78 0.00 0.00 31650.0 56333592.0 0.17 0.02
2021-09-01 17.83 17.88 17.88 17.83 0.22 0.04 36280.0 64831004.0 0.28 0.02
2021-09-02 18.37 18.40 18.44 18.34 0.22 0.04 53423.0 98264475.0 0.54 0.03
2021-09-03 18.06 18.04 18.07 18.04 -0.11 -0.02 24983.0 45082686.0 0.17 0.01
2021-09-04 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2021-09-05 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2021-09-06 18.46 18.45 18.47 18.45 0.00 0.00 23588.0 43525979.0 0.11 0.01
2021-09-07 19.22 19.24 19.25 19.20 0.16 0.03 32054.0 61625241.0 0.26 0.02
2021-09-08 19.21 19.23 19.23 19.19 0.16 0.03 16550.0 31803231.0 0.21 0.01
2021-09-09 18.97 19.00 19.00 18.97 0.16 0.03 19752.0 37520759.0 0.16 0.01
2021-09-10 20.60 20.57 20.62 20.57 -0.15 -0.03 38082.0 78398933.0 0.24 0.02
2021-09-11 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2021-09-12 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2021-09-13 20.20 20.21 20.22 20.19 0.05 0.01 17593.0 35555623.0 0.15 0.01

低频 -> 高频

将 df2 的 5分钟 数据改为 3分钟，缺失数据向前填充

df_3min = df2.set_index('时间').resample('3min').last()
df_3min.ffill()
开盘 收盘 最高 最低 涨跌幅 涨跌额 成交量 成交额 振幅 换手率
时间
2021-08-03 09:33:00 17.99 17.78 18.02 17.75 -1.28 -0.23 52807.0 94339287.0 1.50 0.03
2021-08-03 09:36:00 17.99 17.78 18.02 17.75 -1.28 -0.23 52807.0 94339287.0 1.50 0.03
2021-08-03 09:39:00 17.77 17.76 17.83 17.66 -0.11 -0.02 41508.0 73683531.0 0.96 0.02
2021-08-03 09:42:00 17.77 17.76 17.83 17.66 -0.11 -0.02 41508.0 73683531.0 0.96 0.02
2021-08-03 09:45:00 17.77 17.77 17.83 17.73 0.06 0.01 18521.0 32915794.0 0.56 0.01
... ... ... ... ... ... ... ... ... ... ...
2021-09-13 14:48:00 20.22 20.21 20.26 20.18 0.00 0.00 24419.0 49373556.0 0.40 0.01
2021-09-13 14:51:00 20.22 20.21 20.26 20.18 0.00 0.00 24419.0 49373556.0 0.40 0.01
2021-09-13 14:54:00 20.21 20.20 20.23 20.19 -0.05 -0.01 20769.0 41974013.0 0.20 0.01
2021-09-13 14:57:00 20.21 20.20 20.23 20.19 -0.05 -0.01 20769.0 41974013.0 0.20 0.01
2021-09-13 15:00:00 20.20 20.21 20.22 20.19 0.05 0.01 17593.0 35555623.0 0.15 0.01

19790 rows × 10 columns

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