如何使用xlrd在python中按列名读取Excel数据

Question

我正在尝试读取大型 excel 文件（将近 100000 行）的数据。我在 python 中使用“xlrd 模块”从 excel 中获取数据。我想按列名（ Cascade、Schedule Name、Market ）而不是列号（ 0,1,2 ）获取数据。因为我的excel列不是固定的。我知道如何在固定列的情况下获取数据。

这是我从固定列的 excel 中获取数据的代码

import xlrd

file_location =r"C:\Users\Desktop\Vision.xlsx"
workbook=xlrd.open_workbook(file_location)
sheet= workbook.sheet_by_index(0)
print(sheet.ncols,sheet.nrows,sheet.name,sheet.number)

for i in range(sheet.nrows):
   flag = 0
   for j in range(sheet.ncols):
      value=sheet.cell(i,j).value

如果有人对此有任何解决方案，请告诉我

谢谢

原文由 Sat.N 发布，翻译遵循 CC BY-SA 4.0 许可协议

Answer 1

评论：当标题为

fieldnames = ['Cascade', 'Market', 'Schedule', 'Name] 和

Sheet(['Cascade', 'Schedule', 'Name', 'Market']) 相等。

保持 fieldnames 在 col_idx --- 中的顺序，不是我最初的目标。

---

问题：我想按列名获取数据

以下 OOP 解决方案将起作用：

 class OrderedByName():
    """
    Privides a generator method, to iterate in Column Name ordered sequence
    Provides subscription, to get columns index by name. using class[name]
    """
    def __init__(self, sheet, fieldnames, row=0):
        """
        Create a OrderedDict {name:index} from 'fieldnames'
        :param sheet: The Worksheet to use
        :param fieldnames: Ordered List of Column Names
        :param row: Default Row Index for the Header Row
        """
        from collections import OrderedDict
        self.columns = OrderedDict().fromkeys(fieldnames, None)
        for n in range(sheet.ncols):
            self.columns[sheet.cell(row, n).value] = n

    @property
    def ncols(self):
        """
        Generator, equal usage as range(xlrd.ncols),
          to iterate columns in ordered sequence
        :return: yield Column index
        """
        for idx in self.columns.values():
            yield idx

    def __getitem__(self, item):
        """
        Make class object subscriptable
        :param item: Column Name
        :return: Columns index
        """
        return self.columns[item]

用法：

 # Worksheet Data
sheet([['Schedule', 'Cascade', 'Market'],
       ['SF05UB0', 'DO Macro Upgrade', 'Upper Cnetral Valley'],
       ['DE03HO0', 'DO Macro Upgrade', 'Toledo'],
       ['SF73XC4', 'DO Macro Upgrade', 'SF Bay']]
      )

# Instantiate with Ordered List of Column Names
# NOTE the different Order of Column Names
by_name = OrderedByName(sheet, ['Cascade', 'Market', 'Schedule'])

# Iterate all Rows and all Columns Ordered as instantiated
for row in range(sheet.nrows):
    for col in by_name.ncols:
        value = sheet.cell(row, col).value
        print("cell({}).value == {}".format((row,col), value))

输出：

 cell((0, 1)).value == Cascade
cell((0, 2)).value == Market
cell((0, 0)).value == Schedule
cell((1, 1)).value == DO Macro Upgrade
cell((1, 2)).value == Upper Cnetral Valley
cell((1, 0)).value == SF05UB0
cell((2, 1)).value == DO Macro Upgrade
cell((2, 2)).value == Toledo
cell((2, 0)).value == DE03HO0
cell((3, 1)).value == DO Macro Upgrade
cell((3, 2)).value == SF Bay
cell((3, 0)).value == SF73XC4

---

按名称获取 一 列的索引

print("cell{}.value == {}".format((1, by_name['Schedule']),
                                    sheet.cell(1, by_name['Schedule']).value))
#>>> cell(1, 0).value == SF05UB0

用 Python 测试：3.5

原文由 stovfl 发布，翻译遵循 CC BY-SA 4.0 许可协议

Answer 2

或者，您也可以使用 pandas ，这是一个具有内置 excel I/O 功能 的综合数据分析库。

 import pandas as pd

file_location =r"C:\Users\esatnir\Desktop\Sprint Vision.xlsx"

# Read out first sheet of excel file and return as pandas dataframe
df = pd.read_excel(file_location)

# Reduce dataframe to target columns (by filtering on column names)
df = df[['Cascade', 'Schedule Name', 'Market']]

快速查看生成的数据 df 将显示：

 In [1]: df
Out[1]:
   Cascade     Schedule Name                Market
0  SF05UB0  DO Macro Upgrade  Upper Central Valley
1  DE03HO0  DO Macro Upgrade                Toledo
2  SF73XC4  DO Macro Upgrade                SF Bay

原文由 Xukrao 发布，翻译遵循 CC BY-SA 4.0 许可协议