case (law)
A company, which has 2 data files, now needs to analyze them and process them to calculate the daily sales and present them in the form of bar charts.
demand analysis
Implementation steps
- Design a class that can accomplish the encapsulation of data
- Design an abstract class that defines the functionality associated with file reading and use subclasses to implement the specific functionality
- Reading files and producing data objects
- Perform logical calculations of data requirements (calculate sales for each day)
- Graphing through PyEcharts
coding
Example 1
"""
Classes for data definitions
"""
class Record:
def __init__(self,data,order_id,money,province):
=data
self.order_id=order_id
=money
=province
def __str__(self):
return f"{},{self.order_id},{},{}"
Example 2
"""
Class definitions related to documents
"""
import json
from data_define import Record
class FileReader:
def read_data(self):
# Read the file data, read each piece of data are converted to Record objects, they are encapsulated in a list can return
pass
class TextFileReader(FileReader):
def __init__(self,path):
=path
# Rewrite (implement abstract methods) of the parent class
def read_data(self):
f=open(,"r",encoding="utf-8")
record_list=[]
for line in ():
line=()# Eliminate "\n" from each line of data read.
data_list=(",")
record=Record(data_list[0],data_list[1],int(data_list[2]),data_list[3])
record_list.append(record)
()
return record_list
class JsonFileReader(FileReader):
def __init__(self,path):
=path
# Rewrite (implement abstract methods) of the parent class
def read_data(self):
f=open(,"r",encoding="utf-8")
record_list=[]
for line in ():
data_dict=(line)
record=Record(data_dict["date"],data_dict["order_id"],int(data_dict["money"]),data_dict["province"])
record_list.append(record)
()
return record_list
if __name__ == '__main__':
text_file_reader=TextFileReader("D:/January 2011 Sales Data.txt")
list1=text_file_reader.read_data()
for l in list1:
print(l)
print("========================================================================")
json_file_reader=JsonFileReader("D:/February 2011 Sales Data")
list2=json_file_reader.read_data()
for l in list2:
print(l)
Example 3
from import Bar
from import *
from import *
from file_define import FileReader,TextFileReader,JsonFileReader
from data_define import Record
text_file_reader=TextFileReader("D:/January 2011 Sales Data.txt")
json_file_reader=JsonFileReader("D:/February 2011 Sales Data")
jan_data=text_file_reader.read_data()
feb_data=json_file_reader.read_data()
all_data:list[Record]=jan_data+feb_data
# Starting to do the data calculations
data_dict={}
for record in all_data:
if in data_dict.keys():
data_dict[]+=
else:
data_dict[]=
#Visualization
bar = Bar(init_opts=InitOpts(theme=))
bar.add_xaxis(list(data_dict.keys()))
bar.add_yaxis("Sales",list(data_dict.values()),label_opts=LabelOpts(is_show=False))
bar.set_global_opts(
title_opts=TitleOpts(title="Daily sales")
)
("DailySalesBarChart.html.")
visualization
data set
Link:/s/1P3n-gvooVvmHEPak-xmkKg
Extract code: hxvn
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