[英]How to read Excel data by column name in python using xlrd
I am trying to read the data of large excel file(almost 100000 row).我正在尝试读取大型 excel 文件(近 100000 行)的数据。 I am using 'xlrd Module' in python to fetch the data from excel.我在python中使用'xlrd Module'从excel中获取数据。 I want to fetch data by column name( Cascade,Schedule Name,Market ) instead of column number( 0,1,2 ).我想按列名( Cascade,Schedule Name,Market )而不是列号( 0,1,2 )获取数据。 Because my excel columns are not fixed.因为我的excel列不是固定的。 i know how to fetch data in case of fixed column.我知道如何在固定列的情况下获取数据。
here is the code by which i am fetching data from the excel for fixed column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
If anyone has any solution of this, kindly let me know如果有人对此有任何解决方案,请告诉我
Thanks谢谢
Alternatively you could also make use of pandas
, which is a comprehensive data analysis library with built-in excel I/O capabilities .或者,您也可以使用pandas
,它是一个具有内置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']]
where a quick view of the resulting dataframe df
will show:结果数据帧df
的快速视图将显示:
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
Your column names are in the first row of the spreadsheet, right?您的列名在电子表格的第一行,对吗? So read the first row and construct a mapping from names to column indices.因此,读取第一行并构建从名称到列索引的映射。
column_pos = [ (sheet.cell(0, i).value, i) for i in range(sheet.ncols) ]
colidx = dict(column_pos)
Or as a one-liner:或者作为单线:
colidx = dict( (sheet.cell(0, i).value, i) for i in range(sheet.ncols) )
You can then use the index to interpret column names, for example:然后您可以使用索引来解释列名,例如:
print(sheet.cell(5, colidx["Schedule Name"]).value)
To get an entire column, you can use a list comprehension:要获得一整列,您可以使用列表理解:
schedule = [ sheet.cell(i, colidx["Schedule Name"]).value for i in range(1, sheet.nrows) ]
If you really wanted to, you could create a wrapper for the cell
function that handles the interpretation.如果您真的愿意,可以为处理解释的cell
函数创建一个包装器。 But I think this is simple enough.但我认为这很简单。
Comment : still not working when header of评论:标题时仍然无法正常工作
fieldnames = ['Cascade', 'Market', 'Schedule', 'Name]
andfieldnames = ['Cascade', 'Market', 'Schedule', 'Name]
和Sheet(['Cascade', 'Schedule', 'Name', 'Market'])
are equal.Sheet(['Cascade', 'Schedule', 'Name', 'Market'])
是相等的。
Keep order of fieldnames
in col_idx
, was not my initial goal.在col_idx
保持fieldnames
的col_idx
,这不是我最初的目标。
Question : I want to fetch data by column name问题:我想按列名获取数据
The following OOP
solution will work: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]
Usage :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))
Output :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
Get Index of one Column by Name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
Tested with Python: 3.5用 Python 测试:3.5
You can make use of pandas.您可以使用熊猫。 Below is the sample code for identifying the columns and rows in an excel sheet.下面是用于识别 Excel 工作表中的列和行的示例代码。
import pandas as pd
file_location =r"Your_Excel_Path"
# Read out first sheet of excel file and return as pandas dataframe
df = pd.read_excel(file_location)
total_rows=len(df.axes[0])
total_cols=len(df.axes[1])
# Print total number of rows in an excel sheet
print("Number of Rows: "+str(total_rows))
# Print total number of columns in an excel sheet
print("Number of Columns: "+str(total_cols))
# Print column names in an excel sheet
print(df.columns.ravel())
Now once you have the column data, you can convert it into a list of values.现在,一旦您拥有列数据,就可以将其转换为值列表。
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