无法使用 Pandas read_excel() 为 xlsx 文件下载完整行 [重复]

Question

该文件应该有数千行。 但是在下面使用它只会返回数据框中的前几行

文件 https://www.hkex.com.hk/eng/services/trading/securities/securitieslists/ListOfSecurities.xlsx

失败的例子

import pandas as pd

url = 'https://www.hkex.com.hk/eng/services/trading/securities/securitieslists/ListOfSecurities.xlsx'
df = pd.read_excel(url, engine='openpyxl', header=2, usecols='A:D', verbose=True)
print(df.shape)

# output - only 5 rows
Reading sheet 0
(5, 4)

工作示例

同一个文件。先下载，在Excel中打开，修改文本并保存（没有改变格式并保留xlsx），然后使用read_excel()从文件中打开

url = 'https://www.hkex.com.hk/eng/services/trading/securities/securitieslists/ListOfSecurities.xlsx'
path = os.path.join(os.path.dirname(__file__), 'download')
wget.download(url, out=path)
file = os.path.join(path, 'ListOfSecurities.xlsx')

# open to edit and then save in Excel

df = pd.read_excel(file, engine='openpyxl', header=2, usecols='A:D', verbose=True)
print(df.shape)

# output
Reading sheet 0
(17490, 4)

Answer 1

更新：根据上下文更改代码，xlrd 不可行

import pandas as pd
import os 
import wget

url = 'https://www.hkex.com.hk/eng/services/trading/securities/securitieslists/ListOfSecurities.xlsx'
path = os.path.join(os.path.dirname(__file__), 'download')
wget.download(url, out=path)
filename = os.path.join(path, 'ListOfSecurities.xlsx')

from openpyxl import load_workbook

excel_file = load_workbook(filename)
sheet = excel_file["ListOfSecurities"]
sheet.delete_cols(5,21) # Use only Cols A:D

data = sheet.values
cols = next(data) # Skip row 0
cols = next(data) # Skip row 1
cols = next(data)[0:4] # Cols A:D


df = pd.DataFrame(data, columns=cols)

print(df.shape)

我将 excel 引擎更改为在 pandas 中使用默认引擎 (xlrd)，以下代码有效。

import pandas as pd
import os 
import wget

url = 'https://www.hkex.com.hk/eng/services/trading/securities/securitieslists/ListOfSecurities.xlsx'
path = os.path.join(os.path.dirname(__file__), 'download')
wget.download(url, out=path)
filename = os.path.join(path, 'ListOfSecurities.xlsx')

df = pd.read_excel(filename, header=2, usecols='A:D', verbose=True)
print(df.shape)

输出中的一个不一致之处是它显示的行数减少了 4：

Reading sheet 0
(17486, 4)