python - 如果数据未排序，则无法将 DataFrame 与日期索引拼接

Question

问题

无法根据日期索引拼接数据。我想在'2020-07-20' 此脚本上获取数据，首先读取 output.csv，然后创建DataFrame并放置列“BidClose”，最后打印出特定日期范围的数据AskClose（现在失败了）

解决方案

为了使用 data[start:end] 格式拼接数据，其中start,end是日期范围，必须首先对数据进行排序。 data.sort_index(inplace=True)

import pandas as pd
import numpy as np
import time

datafile = 'output.csv'
data = pd.read_csv(datafile, index_col = 'Date')

# Selects the columns
close = data['BidClose']
askClose = data['AskClose']
# Converts the date strings in the index into pandas datetime format:
close.index = pd.to_datetime(close.index)
askClose.index = pd.to_datetime(askClose.index)

priceSma_df = pd.DataFrame({
      'BidClose' : close,
      'AskClose' : askClose
     })

print(priceSma_df['2020-07-20':'2020-07-20']['AskClose']) #<-- this line failed, shows Empty DataFrame

数据文件

这是数据文件output.csv

Date,BidOpen,BidHigh,BidLow,BidClose,AskOpen,AskHigh,AskLow,AskClose,Vol
07.20.2020 00:17:00,1808.85,1809.01,1808.85,1808.94,1809.2,1809.36,1809.18,1809.25,55
07.20.2020 00:16:00,1808.88,1808.95,1808.82,1808.85,1809.18,1809.31,1809.16,1809.2,77
07.20.2020 00:15:00,1808.83,1808.89,1808.53,1808.88,1809.18,1809.22,1808.87,1809.18,109
07.20.2020 00:14:00,1808.79,1808.88,1808.77,1808.83,1809.13,1809.23,1809.1,1809.18,78
07.20.2020 00:13:00,1808.8,1808.89,1808.78,1808.79,1809.16,1809.28,1809.1,1809.13,91
07.20.2020 00:12:00,1808.79,1808.8,1808.67,1808.8,1809.14,1809.16,1809.01,1809.16,87
07.20.2020 00:11:00,1808.77,1808.92,1808.77,1808.79,1809.15,1809.27,1809.12,1809.14,68
07.20.2020 00:10:00,1808.89,1808.93,1808.55,1808.77,1809.23,1809.3,1808.88,1809.15,167
07.20.2020 00:09:00,1808.55,1808.93,1808.39,1808.89,1809.11,1809.29,1809.02,1809.23,123
07.20.2020 00:08:00,1808.37,1808.57,1808.37,1808.55,1808.96,1809.19,1808.96,1809.11,66
07.20.2020 00:07:00,1808.1,1808.49,1808.0,1808.37,1808.71,1809.15,1808.62,1808.96,147
07.20.2020 00:06:00,1808.84,1808.95,1808.02,1808.1,1809.51,1809.57,1808.54,1808.71,145
07.20.2020 00:05:00,1808.99,1809.0,1808.79,1808.84,1809.64,1809.64,1809.42,1809.51,69
07.20.2020 00:04:00,1808.86,1809.06,1808.79,1808.99,1809.4,1809.65,1809.4,1809.64,82
07.20.2020 00:03:00,1809.17,1809.17,1808.49,1808.86,1809.69,1809.72,1809.0,1809.4,154
07.20.2020 00:02:00,1809.04,1809.23,1809.04,1809.17,1809.52,1809.7,1809.5,1809.69,36
07.20.2020 00:01:00,1808.97,1809.21,1808.94,1809.04,1809.44,1809.64,1809.44,1809.52,77
07.20.2020 00:00:00,1808.9,1809.22,1808.81,1808.97,1809.37,1809.64,1809.29,1809.44,74
07.19.2020 23:59:00,1808.94,1808.95,1808.9,1808.9,1809.4,1809.43,1809.36,1809.37,18
07.19.2020 23:58:00,1808.98,1808.98,1808.76,1808.94,1809.41,1809.41,1809.28,1809.4,36
07.19.2020 23:57:00,1808.93,1809.02,1808.93,1808.98,1809.37,1809.41,1809.37,1809.41,6
07.19.2020 23:56:00,1809.1,1809.1,1808.77,1808.93,1809.47,1809.47,1809.26,1809.37,70
07.19.2020 23:55:00,1809.2,1809.22,1809.09,1809.1,1809.6,1809.6,1809.47,1809.47,35
07.19.2020 23:54:00,1809.13,1809.22,1809.08,1809.2,1809.52,1809.6,1809.5,1809.6,47
07.19.2020 23:53:00,1809.18,1809.21,1809.12,1809.13,1809.59,1809.61,1809.51,1809.52,21
07.19.2020 23:52:00,1809.1,1809.23,1809.09,1809.18,1809.53,1809.62,1809.52,1809.59,28
07.19.2020 23:51:00,1808.94,1809.1,1808.94,1809.1,1809.52,1809.62,1809.5,1809.53,43
07.19.2020 23:50:00,1809.0,1809.0,1808.92,1808.94,1809.55,1809.58,1809.49,1809.52,36
07.19.2020 23:49:00,1809.04,1809.1,1809.0,1809.0,1809.56,1809.59,1809.54,1809.55,40
07.19.2020 23:48:00,1809.01,1809.06,1808.99,1809.04,1809.57,1809.58,1809.56,1809.56,11
07.19.2020 23:47:00,1809.09,1809.16,1809.01,1809.01,1809.67,1809.68,1809.56,1809.57,29
07.19.2020 23:46:00,1809.29,1809.38,1809.09,1809.09,1809.82,1809.88,1809.66,1809.67,33
07.19.2020 23:45:00,1809.33,1809.33,1809.16,1809.29,1809.87,1809.89,1809.74,1809.82,31
07.19.2020 23:44:00,1809.32,1809.37,1809.27,1809.33,1809.85,1809.87,1809.83,1809.87,14
07.19.2020 23:43:00,1809.19,1809.37,1809.19,1809.32,1809.74,1809.89,1809.74,1809.85,46
07.19.2020 23:42:00,1809.26,1809.27,1809.08,1809.19,1809.74,1809.78,1809.65,1809.74,55
07.19.2020 23:41:00,1809.12,1809.26,1809.11,1809.26,1809.65,1809.74,1809.6,1809.74,27
07.19.2020 23:40:00,1809.18,1809.18,1809.12,1809.12,1809.84,1809.86,1809.65,1809.65,15
07.19.2020 23:39:00,1809.37,1809.39,1809.18,1809.18,1809.98,1809.99,1809.84,1809.84,16
07.19.2020 23:38:00,1809.37,1809.46,1809.31,1809.37,1809.98,1809.99,1809.98,1809.98,11
07.19.2020 23:37:00,1809.26,1809.37,1809.26,1809.37,1809.79,1809.99,1809.78,1809.98,16
07.19.2020 23:36:00,1809.31,1809.45,1809.18,1809.26,1809.72,1809.9,1809.68,1809.79,40
07.19.2020 23:35:00,1809.13,1809.36,1809.13,1809.31,1809.59,1809.75,1809.57,1809.72,67
07.19.2020 23:34:00,1809.23,1809.35,1809.07,1809.13,1809.68,1809.84,1809.57,1809.59,129
07.19.2020 23:33:00,1809.55,1809.55,1809.12,1809.23,1810.03,1810.03,1809.63,1809.68,115
07.19.2020 23:32:00,1809.87,1809.89,1809.51,1809.55,1810.34,1810.39,1810.03,1810.03,106
07.19.2020 23:31:00,1810.25,1810.28,1809.81,1809.87,1810.73,1810.75,1810.34,1810.34,81
07.19.2020 23:30:00,1810.11,1810.27,1809.98,1810.25,1810.58,1810.75,1810.52,1810.73,87
07.19.2020 23:29:00,1809.78,1810.15,1809.78,1810.11,1810.3,1810.65,1810.28,1810.58,103
07.19.2020 23:28:00,1809.79,1809.79,1809.74,1809.78,1810.33,1810.34,1810.28,1810.3,11
07.19.2020 23:27:00,1809.68,1809.81,1809.68,1809.79,1810.3,1810.34,1810.3,1810.33,41
07.19.2020 23:26:00,1809.8,1809.84,1809.68,1809.68,1810.38,1810.38,1810.29,1810.3,47
07.19.2020 23:25:00,1809.88,1809.92,1809.7,1809.8,1810.41,1810.45,1810.34,1810.38,91
07.19.2020 23:24:00,1809.83,1809.95,1809.83,1809.88,1810.36,1810.44,1810.36,1810.41,35
07.19.2020 23:23:00,1809.92,1809.98,1809.72,1809.83,1810.44,1810.5,1810.32,1810.36,69
07.19.2020 23:22:00,1809.78,1809.92,1809.72,1809.92,1810.31,1810.47,1810.31,1810.44,31
07.19.2020 23:21:00,1809.89,1809.89,1809.67,1809.78,1810.46,1810.46,1810.24,1810.31,93
07.19.2020 23:20:00,1809.95,1810.03,1809.84,1809.89,1810.54,1810.56,1810.43,1810.46,66
07.19.2020 23:19:00,1810.1,1810.11,1809.92,1809.95,1810.62,1810.67,1810.54,1810.54,49
07.19.2020 23:18:00,1810.21,1810.24,1809.98,1810.1,1810.78,1810.78,1810.58,1810.62,87
07.19.2020 23:17:00,1810.38,1810.38,1810.1,1810.21,1810.84,1810.84,1810.62,1810.78,71
07.19.2020 23:16:00,1810.5,1810.54,1810.31,1810.38,1811.0,1811.01,1810.8,1810.84,98
07.19.2020 23:15:00,1810.36,1810.67,1810.36,1810.5,1810.73,1811.1,1810.73,1811.0,110
07.19.2020 23:14:00,1810.45,1810.49,1810.34,1810.36,1810.95,1810.96,1810.72,1810.73,63
07.19.2020 23:13:00,1810.52,1810.6,1810.34,1810.45,1810.95,1811.04,1810.92,1810.95,116
 

标签： pythonpandasdataframe

Answer 1

您没有使用日期列。这应该有效：

expected_df= (priceSma_df['Date'] >= '2020-07-20') & (priceSma_df['Date'] <= '2020-07-20')