如何在 Python 中处理来自 xlsx 文件的数据

Question

These are the named ranges in an uploaded xlsx sheet, the titles are annoying and I wanted to classify them for easier calling in throughout the code.

Fairly new, and unsure how I would be able to make the below look cleaner and be more efficient if I was going to add more named ranges

VIC_Male = 'Estimated Resident Population ;  Male ;  Victoria ;'
QL_Male = 'Estimated Resident Population ;  Male ;  Queensland ;'
SA_Male = 'Estimated Resident Population ;  Male ;  South Australia ;'
WA_Male = 'Estimated Resident Population ;  Male ;  Western Australia ;'
TAS_Male = 'Estimated Resident Population ;  Male ;  Tasmania ;'
NT_Male = 'Estimated Resident Population ;  Male ;  Northern Territory ;'
ACT_Male = 'Estimated Resident Population ;  Male ;  Australian Capital Territory ;'
TOTAL_Male = 'Estimated Resident Population ;  Male ;  Australia ;'
NSW_Female = 'Estimated Resident Population ;  Female ;  New South Wales ;'
VIC_Female = 'Estimated Resident Population ;  Female ;  Victoria ;'
QL_Female = 'Estimated Resident Population ;  Female ;  Queensland ;'
SA_Female = 'Estimated Resident Population ;  Female ;  South Australia ;'
WA_Female = 'Estimated Resident Population ;  Female ;  Western Australia ;'
TAS_Female = 'Estimated Resident Population ;  Female ;  Tasmania ;'
NT_Female = 'Estimated Resident Population ;  Female ;  Northern Territory ;'
ACT_Female = 'Estimated Resident Population ;  Female ;  Australian Capital Territory ;'
TOTAL_Female = 'Estimated Resident Population ;  Female ;  Australia ;'
NSW_Persons = 'Estimated Resident Population ;  Persons ;  New South Wales ;'
VIC_Persons = 'Estimated Resident Population ;  Persons ;  Victoria ;'
QL_Persons = 'Estimated Resident Population ;  Persons ;  Queensland ;'
SA_Persons = 'Estimated Resident Population ;  Persons ;  South Australia ;'
WA_Persons = 'Estimated Resident Population ;  Persons ;  Western Australia ;'
TAS_Persons = 'Estimated Resident Population ;  Persons ;  Tasmania ;'
NT_Persons = 'Estimated Resident Population ;  Persons ;  Northern Territory ;'
ACT_Persons = 'Estimated Resident Population ;  Persons ;  Australian Capital Territory ;'
TOTAL_Persons = 'Estimated Resident Population ;  Persons ;  Australia ;'```

Answer 1

Let's say you have this csv file (I added titles here in the first line but you can also have the same file without title, in the code bellow i commented the line that you can remove if you do not have titles):

"ResultType;Gender;Country
Estimated Resident Population ;  Male ;  Victoria ;
Estimated Resident Population ;  Male ;  Queensland ;
Estimated Resident Population ;  Male ;  South Australia ;
Estimated Resident Population ;  Male ;  Western Australia ;
Estimated Resident Population ;  Male ;  Tasmania ;
Estimated Resident Population ;  Male ;  Northern Territory ;
"

You can begin by making a data structure that corresponds to your data:

class Record():
    def __init__(self, ResultType, Gender, Country):
        self.ResultType = ResultType
        self.Gender = Gender
        self.Country = Country

Then create an empty list

My_records = []

Then open the csv file with the csv library and for each line of it create an instance of your data structure (here the Record class).

with open('records.txt') as csv_file:

    csv_reader = csv.reader(csv_file, delimiter=';')
    line_count = 0
    for row in csv_reader:
        #You can remove this part if your csv file has no column name lines
        if line_count == 0:
            print(f'Column names are {", ".join(row)}') #
            line_count += 1
        else:
            instance = Record(row[0], row[1], row[2])
            My_records.append(instance)

All in one:

import csv

class Record():
    def __init__(self, ResultType, Gender, Country):
        self.ResultType = ResultType
        self.Gender = Gender
        self.Country = Country
My_records = []
with open('records.txt') as csv_file:

    csv_reader = csv.reader(csv_file, delimiter=';')
    line_count = 0
    for row in csv_reader:
        if line_count == 0:
            print(f'Column names are {", ".join(row)}')
            line_count += 1
        else:
            instance = Record(row[0], row[1], row[2])
            My_records.append(instance)

Now the My_records list is a list filled with each line of your CSV file as an instance of class Record. Thus you can manipulate it as you wish.

For example:

All_countries = set([record.Country.strip() for record in My_records])
print(All_countries)

OUTPUT (All unique country present in your data):

{'Northern Territory', 'Tasmania', 'South Australia', 'Queensland', 'Western Australia', 'Australia', 'Australian Capital Territory', 'New South Wales', 'Victoria'}

Of course you have many usefull libraries that aims to deal with those kind of stuff, like pandas but here I gave you example in plain python (using the csv included library though)

By the way, if your file is an xls file, those libraries (like pandas) has this kind of tools (but you'll have to pip install pandas first):

import pandas as pd
dfs = pd.read_excel("record.xlsx", sheet_name="sheet1")

This code will actually replace the lines in the above example:

with open('records.txt') as csv_file:

    csv_reader = csv.reader(csv_file, delimiter=';')
    ...

The rest is the same.

Answer 2

Maybe something like this:

VIC_Male       = 'Estimated Resident Population ;  Male ;  Victoria ;'
QL_Male        = 'Estimated Resident Population ;  Male ;  Queensland ;'
SA_Male        = 'Estimated Resident Population ;  Male ;  South Australia ;'
WA_Male        = 'Estimated Resident Population ;  Male ;  Western Australia ;'
TAS_Male       = 'Estimated Resident Population ;  Male ;  Tasmania ;'
NT_Male        = 'Estimated Resident Population ;  Male ;  Northern Territory ;'
ACT_Male       = 'Estimated Resident Population ;  Male ;  Australian Capital Territory ;'
TOTAL_Male     = 'Estimated Resident Population ;  Male ;  Australia ;'
NSW_Female     = 'Estimated Resident Population ;  Female ;  New South Wales ;'
VIC_Female     = 'Estimated Resident Population ;  Female ;  Victoria ;'
QL_Female      = 'Estimated Resident Population ;  Female ;  Queensland ;'
SA_Female      = 'Estimated Resident Population ;  Female ;  South Australia ;'
WA_Female      = 'Estimated Resident Population ;  Female ;  Western Australia ;'
TAS_Female     = 'Estimated Resident Population ;  Female ;  Tasmania ;'
NT_Female      = 'Estimated Resident Population ;  Female ;  Northern Territory ;'
ACT_Female     = 'Estimated Resident Population ;  Female ;  Australian Capital Territory ;'
TOTAL_Female   = 'Estimated Resident Population ;  Female ;  Australia ;'
NSW_Persons    = 'Estimated Resident Population ;  Persons ;  New South Wales ;'
VIC_Persons    = 'Estimated Resident Population ;  Persons ;  Victoria ;'
QL_Persons     = 'Estimated Resident Population ;  Persons ;  Queensland ;'
SA_Persons     = 'Estimated Resident Population ;  Persons ;  South Australia ;'
WA_Persons     = 'Estimated Resident Population ;  Persons ;  Western Australia ;'
TAS_Persons    = 'Estimated Resident Population ;  Persons ;  Tasmania ;'
NT_Persons     = 'Estimated Resident Population ;  Persons ;  Northern Territory ;'
ACT_Persons    = 'Estimated Resident Population ;  Persons ;  Australian Capital Territory ;'
TOTAL_Persons  = 'Estimated Resident Population ;  Persons ;  Australia ;'```