Python formatting and processing of one-dimensional and two-dimensional data

Introduction to this chapter

What is data formatting

Preface:
-After studying this chapter, you will have a standardized/formatted perspective on data
-Methodology: Understanding files and data representation from a Python perspective
-Practical ability: Learn to write programs with file input and output

1. Dimensions of data organization

Dimension: The organization of a set of data-linear or two-dimensional or higher

One-dimensional data: It is composed of ordered or disordered data in a peer-to-peer relationship, organized in a linear manner

Two-dimensional data: It is composed of multiple one-dimensional data, which is a combination of one-dimensional data (a table is a typical two-dimensional data, and the header is a part of the two-dimensional data)

Multi-dimensional data: the expansion of one-dimensional or two-dimensional data in a new dimension

2. Data operation cycle

Storage <-> means <-> operation-a total of three stages

3. Representation of one-dimensional data

Ordered, use list
Unordered, use set

Both lists and collections can be used to traverse data with for

4. Storage of one-dimensional data

Method 1: Use one or more spaces to separate, without line breaks,
such as: China, the United States, Japan, Italy
Restrictions: no spaces can exist in the data

Method 2: Use English half-width commas to separate without line breaks,
such as: China, the United States, Japan, and Italy.
Restrictions: English commas cannot be included in the data

Other methods: use special symbols to separate

5. One-dimensional data processing

Example 1

f = open("E:/code/python/821/fname.txt",encoding="utf-8")
txt = f.read()
ls = txt.split()
f.close()
print(ls)
输出
['中国', '美国', '日本', '意大利', '德国', '法国', '英国', '意大利']

Example 2

ls = ['新疆','北京','大连']
f = open("E:/code/python/821/fname.txt","w",encoding="utf-8")
f.write(" ".join(ls))
f.close()

View the file at this time

Summary: read-split() write-join()

6. Representation of two-dimensional data

Generally use a two-dimensional list-itself and each element in the list are lists
Use a two-level for loop to traverse each element

7. CSV format and 2D data storage

CSV: Comma-Separated Values-Comma-separated values
-internationally used one and two-dimensional data storage format, general .csv extension
-one one-dimensional data per line, separated by commas, no blank lines-
Excel and general editing software can be used Read or save as a .csv file
Convention
-if an element is missing, the comma still needs to be tabulated
-the header of the two-dimensional data can be stored as data or stored separately

If an element contains a comma, you need to add quotation marks on both sides of the element, indicating that the comma is not used to separate the element

General indexing habits: first row and then column ls[row] column

8. Two-dimensional data processing

Example 1

fo = open(fname)

ls = []

for line in fo:
    line = line.replace("\n","")#根据每行结束都有回车的习惯
    ls.append(line.split(","))#括号内得到由，分隔开的列表

fo.close()

Example 2 Write data to a file in CSV format

ls = [[],[],[]] #二维列表

f = open(fname,'w')

for item in ls:
    f.write(','.join(item) + "\n")
f.close()

Example 3 Traverse

ls = [[1,2],[3,4],[5,6]] #二维列表

for row in ls:
    for column in row:
        print(column)
输出
1
2
3
4
5
6

Source: BIT Python MOOC