如何使用Python将多个excel工作表从网站下载到数据框架中
我试图从网站上Excel表格中存储的历史数据创建一个时间序列。该网站有按年度组织的Excel电子表格（即2009年、2010年、2011年的金融期货头寸等） 是否有一种方法可以一次提取所有相关文件以在数据帧中使用 我对Python非常陌生，我的第一个想法是将每个文件作为Excel文档手动下载，然后用Python将它们读取到DF中。他试图为这个过程找到一个更优雅的解决方案 网站网址：如何使用Python将多个excel工作表从网站下载到数据框架中,python,excel,dataframe,web-scraping,Python,Excel,Dataframe,Web Scraping,我试图从网站上Excel表格中存储的历史数据创建一个时间序列。该网站有按年度组织的Excel电子表格（即2009年、2010年、2011年的金融期货头寸等） 是否有一种方法可以一次提取所有相关文件以在数据帧中使用 我对Python非常陌生，我的第一个想法是将每个文件作为Excel文档手动下载，然后用Python将它们读取到DF中。他试图为这个过程找到一个更优雅的解决方案 网站网址： 该页面有多组文件。我正在试图找到一种方法来选择特定的文件/文件组。我目前正在谷歌上搜索解决方案，包括使用Beaut
该页面有多组文件。我正在试图找到一种方法来选择特定的文件/文件组。我目前正在谷歌上搜索解决方案，包括使用BeautifulSoup或类似的东西来分解网站HTML 可能有一种更优雅的方法可以找到包含所需zip文件/链接的相关表的
import pandas as pd
import requests
from bs4 import BeautifulSoup
from zipfile import ZipFile
from io import BytesIO
url = 'https://www.cftc.gov/MarketReports/CommitmentsofTraders/HistoricalCompressed/index.htm'
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')
# Find the p tag with the specific table you wanted
p_tag = soup.find_all('p')
for p in p_tag:
if 'The complete Commitments of Traders Futures Only reports' in p.text:
break
# Get that table with the zip links
table = p.find_next_sibling('table')
a_tags = table.find_all('a', text = 'Excel')
# Create list of those links
files_list = []
for a in a_tags:
href = 'https://www.cftc.gov' + a['href']
files_list.append(href)
# Iterate through those links, get he table within the zip, and append to a results dataframe
results = pd.DataFrame()
for file_name in files_list[:-1]:
year = file_name.split('_')[-1].split('.')[0]
content = requests.get(file_name)
zf = ZipFile(BytesIO(content.content))
excel_file = zf.namelist()[0]
temp_df = pd.read_excel(zf.open(excel_file))
results = results.append(temp_df, sort=True).reset_index(drop=True)
print ('Recieved: %s' %year)
print (results.head(5).to_string())
As_of_Date_In_Form_YYMMDD CFTC_Commodity_Code CFTC_Contract_Market_Code CFTC_Market_Code CFTC_Region_Code Change_in_Comm_Long_All Change_in_Comm_Short_All Change_in_NonComm_Long_All Change_in_NonComm_Short_All Change_in_NonComm_Spead_All Change_in_NonRept_Long_All Change_in_NonRept_Short_All Change_in_Open_Interest_All Change_in_Tot_Rept_Long_All Change_in_Tot_Rept_Short_All Comm_Positions_Long_All Comm_Positions_Long_Old Comm_Positions_Long_Other Comm_Positions_Short_All Comm_Positions_Short_Old Comm_Positions_Short_Other Conc_Gross_LE_4_TDR_Long_All Conc_Gross_LE_4_TDR_Long_Old Conc_Gross_LE_4_TDR_Long_Other Conc_Gross_LE_4_TDR_Short_All Conc_Gross_LE_4_TDR_Short_Old Conc_Gross_LE_4_TDR_Short_Other Conc_Gross_LE_8_TDR_Long_All Conc_Gross_LE_8_TDR_Long_Old Conc_Gross_LE_8_TDR_Long_Other Conc_Gross_LE_8_TDR_Short_All Conc_Gross_LE_8_TDR_Short_Old Conc_Gross_LE_8_TDR_Short_Other Conc_Net_LE_4_TDR_Long_All Conc_Net_LE_4_TDR_Long_Old Conc_Net_LE_4_TDR_Long_Other Conc_Net_LE_4_TDR_Short_All Conc_Net_LE_4_TDR_Short_Old Conc_Net_LE_4_TDR_Short_Other Conc_Net_LE_8_TDR_Long_All Conc_Net_LE_8_TDR_Long_Old Conc_Net_LE_8_TDR_Long_Other Conc_Net_LE_8_TDR_Short_All Conc_Net_LE_8_TDR_Short_Old Conc_Net_LE_8_TDR_Short_Other Contract_Units Market_and_Exchange_Names NonComm_Positions_Long_All NonComm_Positions_Long_Old NonComm_Positions_Long_Other NonComm_Positions_Short_All NonComm_Positions_Short_Old NonComm_Positions_Short_Other NonComm_Positions_Spread_Old NonComm_Positions_Spread_Other NonComm_Postions_Spread_All NonRept_Positions_Long_All NonRept_Positions_Long_Old NonRept_Positions_Long_Other NonRept_Positions_Short_All NonRept_Positions_Short_Old NonRept_Positions_Short_Other Open_Interest_All Open_Interest_Old Open_Interest_Other Pct_of_OI_Comm_Long_All Pct_of_OI_Comm_Long_Old Pct_of_OI_Comm_Long_Other Pct_of_OI_Comm_Short_All Pct_of_OI_Comm_Short_Old Pct_of_OI_Comm_Short_Other Pct_of_OI_NonComm_Long_All Pct_of_OI_NonComm_Long_Old Pct_of_OI_NonComm_Long_Other Pct_of_OI_NonComm_Short_All Pct_of_OI_NonComm_Short_Old Pct_of_OI_NonComm_Short_Other Pct_of_OI_NonComm_Spread_All Pct_of_OI_NonComm_Spread_Old Pct_of_OI_NonComm_Spread_Other Pct_of_OI_NonRept_Long_All Pct_of_OI_NonRept_Long_Old Pct_of_OI_NonRept_Long_Other Pct_of_OI_NonRept_Short_All Pct_of_OI_NonRept_Short_Old Pct_of_OI_NonRept_Short_Other Pct_of_OI_Tot_Rept_Long_All Pct_of_OI_Tot_Rept_Long_Old Pct_of_OI_Tot_Rept_Long_Other Pct_of_OI_Tot_Rept_Short_All Pct_of_OI_Tot_Rept_Short_Old Pct_of_OI_Tot_Rept_Short_Other Pct_of_Open_Interest_All Pct_of_Open_Interest_Old Pct_of_Open_Interest_Other Report_Date_as_MM_DD_YYYY Tot_Rept_Positions_Long_All Tot_Rept_Positions_Long_Old Tot_Rept_Positions_Long_Other Tot_Rept_Positions_Short_All Tot_Rept_Positions_Short_Old Tot_Rept_Positions_Short_Other Traders_Comm_Long_All Traders_Comm_Long_Old Traders_Comm_Long_Other Traders_Comm_Short_All Traders_Comm_Short_Old Traders_Comm_Short_Other Traders_NonComm_Long_All Traders_NonComm_Long_Old Traders_NonComm_Long_Other Traders_NonComm_Short_All Traders_NonComm_Short_Old Traders_NonComm_Short_Other Traders_NonComm_Spead_Old Traders_NonComm_Spread_All Traders_NonComm_Spread_Other Traders_Tot_All Traders_Tot_Old Traders_Tot_Other Traders_Tot_Rept_Long_All Traders_Tot_Rept_Long_Old Traders_Tot_Rept_Long_Other Traders_Tot_Rept_Short_All Traders_Tot_Rept_Short_Old Traders_Tot_Rept_Short_Other
0 190910 1 001602 CBT 0 -4068.0 4892.0 6487.0 -2906.0 8280.0 -944.0 -511.0 9755.0 10699.0 10266.0 107772 92050 15722 102893 86995 15898 11.9 12.6 31.6 11.6 12.6 26.7 21.1 22.3 46.5 20.0 21.9 39.6 10.8 11.1 31.5 10.0 10.4 23.4 17.4 18.6 45.4 15.5 16.7 36.1 (CONTRACTS OF 5,000 BUSHELS) WHEAT-SRW - CHICAGO BOARD OF TRADE 121056 112747 22502 111727 105822 20098 88722 6159 109074 25816 20362 5454 40024 32342 7682 363718 313881 49837 29.6 29.3 31.5 28.3 27.7 31.9 33.3 35.9 45.2 30.7 33.7 40.3 30.0 28.3 12.4 7.1 6.5 10.9 11.0 10.3 15.4 92.9 93.5 89.1 89.0 89.7 84.6 100 100 100 2019-09-10 337902 293519 44383 323694 281539 42155 80 72 34 92 87 49 101 104 35 115 109 41 103 118 20 346 338 145 252 232 83 262 247 99
1 190903 1 001602 CBT 0 -703.0 -15572.0 -3482.0 13336.0 -702.0 337.0 -1612.0 -4550.0 -4887.0 -2938.0 111840 97821 14019 98001 82374 15627 13.2 13.7 32.6 11.9 13.0 25.9 21.9 22.9 45.3 20.1 22.2 37.7 12.1 12.2 32.6 9.9 10.4 22.2 18.5 19.0 44.3 16.1 17.7 33.7 (CONTRACTS OF 5,000 BUSHELS) WHEAT-SRW - CHICAGO BOARD OF TRADE 114569 103964 22404 114633 108323 18109 83004 5991 100794 26760 21199 5561 40535 32287 8248 353963 305988 47975 31.6 32.0 29.2 27.7 26.9 32.6 32.4 34.0 46.7 32.4 35.4 37.7 28.5 27.1 12.5 7.6 6.9 11.6 11.5 10.6 17.2 92.4 93.1 88.4 88.5 89.4 82.8 100 100 100 2019-09-03 327203 284789 42414 313428 273701 39727 81 74 35 88 84 50 90 94 36 128 123 39 95 110 20 345 338 143 243 222 83 261 250 98
2 190827 1 001602 CBT 0 -18756.0 -10204.0 5094.0 -3903.0 -13782.0 -1379.0 -934.0 -28823.0 -27444.0 -27889.0 112543 101309 11234 113573 98886 14687 12.8 13.1 32.9 12.5 14.3 25.9 20.6 21.8 47.3 21.1 23.2 37.5 11.4 11.6 32.1 9.9 11.2 22.1 17.8 18.7 45.1 16.5 18.4 31.3 (CONTRACTS OF 5,000 BUSHELS) WHEAT-SRW - CHICAGO BOARD OF TRADE 118051 108685 22347 101297 97801 16477 81990 6525 101496 26423 20736 5687 42147 34043 8104 358513 312720 45793 31.4 32.4 24.5 31.7 31.6 32.1 32.9 34.8 48.8 28.3 31.3 36.0 28.3 26.2 14.2 7.4 6.6 12.4 11.8 10.9 17.7 92.6 93.4 87.6 88.2 89.1 82.3 100 100 100 2019-08-27 332090 291984 40106 316366 278677 37689 85 81 30 96 94 51 99 104 35 110 106 38 103 116 20 341 336 139 252 238 76 264 255 99
3 190820 1 001602 CBT 0 8679.0 -1358.0 -5449.0 3109.0 -361.0 -1090.0 389.0 1779.0 2869.0 1390.0 131299 119922 11377 123777 107310 16467 12.2 12.5 30.0 11.0 12.1 26.1 19.9 20.6 46.2 19.7 21.2 37.7 10.0 9.8 29.7 8.4 9.4 22.3 15.8 16.4 43.7 13.9 15.5 32.0 (CONTRACTS OF 5,000 BUSHELS) WHEAT-SRW - CHICAGO BOARD OF TRADE 112957 104967 21051 105200 104347 13914 96015 6202 115278 27802 22317 5485 43081 35549 7532 387336 343221 44115 33.9 34.9 25.8 32.0 31.3 37.3 29.2 30.6 47.7 27.2 30.4 31.5 29.8 28.0 14.1 7.2 6.5 12.4 11.1 10.4 17.1 92.8 93.5 87.6 88.9 89.6 82.9 100 100 100 2019-08-20 359534 320904 38630 344255 307672 36583 95 93 31 98 98 55 98 102 35 113 113 40 118 127 19 350 348 144 271 261 78 273 270 102
4 190813 1 001602 CBT 0 -13926.0 -18764.0 -2482.0 2663.0 4055.0 -1910.0 -2217.0 -14263.0 -12353.0 -12046.0 122620 112079 10541 125135 107483 17652 11.2 11.2 30.6 11.7 12.5 25.1 19.1 19.6 44.8 19.5 21.0 38.1 10.4 10.3 30.0 8.5 10.1 22.9 16.0 16.7 42.2 14.4 16.2 33.3 (CONTRACTS OF 5,000 BUSHELS) WHEAT-SRW - CHICAGO BOARD OF TRADE 118406 110864 21133 102091 103554 12128 96048 6000 115639 28892 23513 5379 42692 35419 7273 385557 342504 43053 31.8 32.7 24.5 32.5 31.4 41.0 30.7 32.4 49.1 26.5 30.2 28.2 30.0 28.0 13.9 7.5 6.9 12.5 11.1 10.3 16.9 92.5 93.1 87.5 88.9 89.7 83.1 100 100 100 2019-08-13 356665 318991 37674 342865 307085 35780 85 83 31 108 106 56 102 107 33 111 108 35 119 127 19 355 352 139 261 252 75 285 279 99
import pandas as pd
import requests
from bs4 import BeautifulSoup
from zipfile import ZipFile
from io import BytesIO
url = 'https://www.cftc.gov/MarketReports/CommitmentsofTraders/HistoricalCompressed/index.htm'
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')
# Find the p tag with the specific table you wanted
p_tag = soup.find_all('p')
for p in p_tag:
if 'The complete Commitments of Traders Futures Only reports' in p.text:
break
# Get that table with the zip links
table = p.find_next_sibling('table')
a_tags = table.find_all('a', text = 'Excel')
# Create list of those links
files_list = []
for a in a_tags:
href = 'https://www.cftc.gov' + a['href']
files_list.append(href)
# Iterate through those links, get he table within the zip, and append to a results dataframe
results = pd.DataFrame()
for file_name in files_list[:-1]:
year = file_name.split('_')[-1].split('.')[0]
content = requests.get(file_name)
zf = ZipFile(BytesIO(content.content))
excel_file = zf.namelist()[0]
temp_df = pd.read_excel(zf.open(excel_file))
results = results.append(temp_df, sort=True).reset_index(drop=True)
print ('Recieved: %s' %year)
print (results.head(5).to_string())
As_of_Date_In_Form_YYMMDD CFTC_Commodity_Code CFTC_Contract_Market_Code CFTC_Market_Code CFTC_Region_Code Change_in_Comm_Long_All Change_in_Comm_Short_All Change_in_NonComm_Long_All Change_in_NonComm_Short_All Change_in_NonComm_Spead_All Change_in_NonRept_Long_All Change_in_NonRept_Short_All Change_in_Open_Interest_All Change_in_Tot_Rept_Long_All Change_in_Tot_Rept_Short_All Comm_Positions_Long_All Comm_Positions_Long_Old Comm_Positions_Long_Other Comm_Positions_Short_All Comm_Positions_Short_Old Comm_Positions_Short_Other Conc_Gross_LE_4_TDR_Long_All Conc_Gross_LE_4_TDR_Long_Old Conc_Gross_LE_4_TDR_Long_Other Conc_Gross_LE_4_TDR_Short_All Conc_Gross_LE_4_TDR_Short_Old Conc_Gross_LE_4_TDR_Short_Other Conc_Gross_LE_8_TDR_Long_All Conc_Gross_LE_8_TDR_Long_Old Conc_Gross_LE_8_TDR_Long_Other Conc_Gross_LE_8_TDR_Short_All Conc_Gross_LE_8_TDR_Short_Old Conc_Gross_LE_8_TDR_Short_Other Conc_Net_LE_4_TDR_Long_All Conc_Net_LE_4_TDR_Long_Old Conc_Net_LE_4_TDR_Long_Other Conc_Net_LE_4_TDR_Short_All Conc_Net_LE_4_TDR_Short_Old Conc_Net_LE_4_TDR_Short_Other Conc_Net_LE_8_TDR_Long_All Conc_Net_LE_8_TDR_Long_Old Conc_Net_LE_8_TDR_Long_Other Conc_Net_LE_8_TDR_Short_All Conc_Net_LE_8_TDR_Short_Old Conc_Net_LE_8_TDR_Short_Other Contract_Units Market_and_Exchange_Names NonComm_Positions_Long_All NonComm_Positions_Long_Old NonComm_Positions_Long_Other NonComm_Positions_Short_All NonComm_Positions_Short_Old NonComm_Positions_Short_Other NonComm_Positions_Spread_Old NonComm_Positions_Spread_Other NonComm_Postions_Spread_All NonRept_Positions_Long_All NonRept_Positions_Long_Old NonRept_Positions_Long_Other NonRept_Positions_Short_All NonRept_Positions_Short_Old NonRept_Positions_Short_Other Open_Interest_All Open_Interest_Old Open_Interest_Other Pct_of_OI_Comm_Long_All Pct_of_OI_Comm_Long_Old Pct_of_OI_Comm_Long_Other Pct_of_OI_Comm_Short_All Pct_of_OI_Comm_Short_Old Pct_of_OI_Comm_Short_Other Pct_of_OI_NonComm_Long_All Pct_of_OI_NonComm_Long_Old Pct_of_OI_NonComm_Long_Other Pct_of_OI_NonComm_Short_All Pct_of_OI_NonComm_Short_Old Pct_of_OI_NonComm_Short_Other Pct_of_OI_NonComm_Spread_All Pct_of_OI_NonComm_Spread_Old Pct_of_OI_NonComm_Spread_Other Pct_of_OI_NonRept_Long_All Pct_of_OI_NonRept_Long_Old Pct_of_OI_NonRept_Long_Other Pct_of_OI_NonRept_Short_All Pct_of_OI_NonRept_Short_Old Pct_of_OI_NonRept_Short_Other Pct_of_OI_Tot_Rept_Long_All Pct_of_OI_Tot_Rept_Long_Old Pct_of_OI_Tot_Rept_Long_Other Pct_of_OI_Tot_Rept_Short_All Pct_of_OI_Tot_Rept_Short_Old Pct_of_OI_Tot_Rept_Short_Other Pct_of_Open_Interest_All Pct_of_Open_Interest_Old Pct_of_Open_Interest_Other Report_Date_as_MM_DD_YYYY Tot_Rept_Positions_Long_All Tot_Rept_Positions_Long_Old Tot_Rept_Positions_Long_Other Tot_Rept_Positions_Short_All Tot_Rept_Positions_Short_Old Tot_Rept_Positions_Short_Other Traders_Comm_Long_All Traders_Comm_Long_Old Traders_Comm_Long_Other Traders_Comm_Short_All Traders_Comm_Short_Old Traders_Comm_Short_Other Traders_NonComm_Long_All Traders_NonComm_Long_Old Traders_NonComm_Long_Other Traders_NonComm_Short_All Traders_NonComm_Short_Old Traders_NonComm_Short_Other Traders_NonComm_Spead_Old Traders_NonComm_Spread_All Traders_NonComm_Spread_Other Traders_Tot_All Traders_Tot_Old Traders_Tot_Other Traders_Tot_Rept_Long_All Traders_Tot_Rept_Long_Old Traders_Tot_Rept_Long_Other Traders_Tot_Rept_Short_All Traders_Tot_Rept_Short_Old Traders_Tot_Rept_Short_Other
0 190910 1 001602 CBT 0 -4068.0 4892.0 6487.0 -2906.0 8280.0 -944.0 -511.0 9755.0 10699.0 10266.0 107772 92050 15722 102893 86995 15898 11.9 12.6 31.6 11.6 12.6 26.7 21.1 22.3 46.5 20.0 21.9 39.6 10.8 11.1 31.5 10.0 10.4 23.4 17.4 18.6 45.4 15.5 16.7 36.1 (CONTRACTS OF 5,000 BUSHELS) WHEAT-SRW - CHICAGO BOARD OF TRADE 121056 112747 22502 111727 105822 20098 88722 6159 109074 25816 20362 5454 40024 32342 7682 363718 313881 49837 29.6 29.3 31.5 28.3 27.7 31.9 33.3 35.9 45.2 30.7 33.7 40.3 30.0 28.3 12.4 7.1 6.5 10.9 11.0 10.3 15.4 92.9 93.5 89.1 89.0 89.7 84.6 100 100 100 2019-09-10 337902 293519 44383 323694 281539 42155 80 72 34 92 87 49 101 104 35 115 109 41 103 118 20 346 338 145 252 232 83 262 247 99
1 190903 1 001602 CBT 0 -703.0 -15572.0 -3482.0 13336.0 -702.0 337.0 -1612.0 -4550.0 -4887.0 -2938.0 111840 97821 14019 98001 82374 15627 13.2 13.7 32.6 11.9 13.0 25.9 21.9 22.9 45.3 20.1 22.2 37.7 12.1 12.2 32.6 9.9 10.4 22.2 18.5 19.0 44.3 16.1 17.7 33.7 (CONTRACTS OF 5,000 BUSHELS) WHEAT-SRW - CHICAGO BOARD OF TRADE 114569 103964 22404 114633 108323 18109 83004 5991 100794 26760 21199 5561 40535 32287 8248 353963 305988 47975 31.6 32.0 29.2 27.7 26.9 32.6 32.4 34.0 46.7 32.4 35.4 37.7 28.5 27.1 12.5 7.6 6.9 11.6 11.5 10.6 17.2 92.4 93.1 88.4 88.5 89.4 82.8 100 100 100 2019-09-03 327203 284789 42414 313428 273701 39727 81 74 35 88 84 50 90 94 36 128 123 39 95 110 20 345 338 143 243 222 83 261 250 98
2 190827 1 001602 CBT 0 -18756.0 -10204.0 5094.0 -3903.0 -13782.0 -1379.0 -934.0 -28823.0 -27444.0 -27889.0 112543 101309 11234 113573 98886 14687 12.8 13.1 32.9 12.5 14.3 25.9 20.6 21.8 47.3 21.1 23.2 37.5 11.4 11.6 32.1 9.9 11.2 22.1 17.8 18.7 45.1 16.5 18.4 31.3 (CONTRACTS OF 5,000 BUSHELS) WHEAT-SRW - CHICAGO BOARD OF TRADE 118051 108685 22347 101297 97801 16477 81990 6525 101496 26423 20736 5687 42147 34043 8104 358513 312720 45793 31.4 32.4 24.5 31.7 31.6 32.1 32.9 34.8 48.8 28.3 31.3 36.0 28.3 26.2 14.2 7.4 6.6 12.4 11.8 10.9 17.7 92.6 93.4 87.6 88.2 89.1 82.3 100 100 100 2019-08-27 332090 291984 40106 316366 278677 37689 85 81 30 96 94 51 99 104 35 110 106 38 103 116 20 341 336 139 252 238 76 264 255 99
3 190820 1 001602 CBT 0 8679.0 -1358.0 -5449.0 3109.0 -361.0 -1090.0 389.0 1779.0 2869.0 1390.0 131299 119922 11377 123777 107310 16467 12.2 12.5 30.0 11.0 12.1 26.1 19.9 20.6 46.2 19.7 21.2 37.7 10.0 9.8 29.7 8.4 9.4 22.3 15.8 16.4 43.7 13.9 15.5 32.0 (CONTRACTS OF 5,000 BUSHELS) WHEAT-SRW - CHICAGO BOARD OF TRADE 112957 104967 21051 105200 104347 13914 96015 6202 115278 27802 22317 5485 43081 35549 7532 387336 343221 44115 33.9 34.9 25.8 32.0 31.3 37.3 29.2 30.6 47.7 27.2 30.4 31.5 29.8 28.0 14.1 7.2 6.5 12.4 11.1 10.4 17.1 92.8 93.5 87.6 88.9 89.6 82.9 100 100 100 2019-08-20 359534 320904 38630 344255 307672 36583 95 93 31 98 98 55 98 102 35 113 113 40 118 127 19 350 348 144 271 261 78 273 270 102
4 190813 1 001602 CBT 0 -13926.0 -18764.0 -2482.0 2663.0 4055.0 -1910.0 -2217.0 -14263.0 -12353.0 -12046.0 122620 112079 10541 125135 107483 17652 11.2 11.2 30.6 11.7 12.5 25.1 19.1 19.6 44.8 19.5 21.0 38.1 10.4 10.3 30.0 8.5 10.1 22.9 16.0 16.7 42.2 14.4 16.2 33.3 (CONTRACTS OF 5,000 BUSHELS) WHEAT-SRW - CHICAGO BOARD OF TRADE 118406 110864 21133 102091 103554 12128 96048 6000 115639 28892 23513 5379 42692 35419 7273 385557 342504 43053 31.8 32.7 24.5 32.5 31.4 41.0 30.7 32.4 49.1 26.5 30.2 28.2 30.0 28.0 13.9 7.5 6.9 12.5 11.1 10.3 16.9 92.5 93.1 87.5 88.9 89.7 83.1 100 100 100 2019-08-13 356665 318991 37674 342865 307085 35780 85 83 31 108 106 56 102 107 33 111 108 35 119 127 19 355 352 139 261 252 75 285 279 99
你的想法是对的。您当然要下载该文件，然后将其读入pandas，然后附加每个附加文件。另一个可能有用的选项是，您可以直接读取表/excel数据，而无需作为文件下载。但是，如果不提供您正在使用的实际url，您将不会得到比我在此评论中发布的内容更多的解决方案。@chitown88谢谢您的反馈。刚刚在原来的帖子中添加了一个更新，以帮助我了解情况。它看起来确实有点棘手，因为文件是.zip文件。这并不意味着这是不可能的，只是需要一个额外的步骤来自动解压缩（这是我以前没有做过的，感谢有机会学习一些新的东西）。我将在稍后对此进行研究，并发布解决方案，我发现它能够将它们附加到1个数据帧中，而无需先写入磁盘。现在正在制定解决方案，并将在一小时内发布。谢谢你在这方面的帮助。我自己也尝试了一些事情，但没有取得多大进展。太棒了！非常感谢你把这些放在一起。这使我达到了一个很好的点，我可以开始操纵DF。目前正在处理每一行，以便我能够更好地了解您是如何解决问题的。学习了很多，所以真的很感激。