Hands on hands to teach you to use Python crawling storage data, but also automatic visualization in Excel!

Watch the corner. 2020-11-14 11:21:30
hands hands teach use python

Hello everyone , We talked about how to use Python Build a with GUI The crawler applet for , A lot of this article will cater to the hot spots , Continuation of the last NBA Reptiles GUI, To explore how to climb the Tiger flutter NBA Official website data .  And write the data to Excel At the same time, the line chart is automatically generated in , There are mainly the following steps

This article will be divided into the following two parts to explain

  • In the tiger NBA Crawler in player page of official website , Get player data .
  • Cleaning and finishing Crawling player data , On the visualization .

The main project involves Python modular :

  • requests
  • pandas
  • bs4


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Many people study python, After mastering the basic grammar , I don't know where to look for cases to start .
A lot of people who have done cases , But I don't know how to learn more advanced knowledge .
So for these three kinds of people , I will provide you with a good learning platform , Get a free video tutorial , electronic text , And the source code of the course !
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   The reptile part

Crawler part of the finishing ideas are as follows

Observe URL1 The source code to find the team name and corresponding URL2 Observe URL2 Source code to find the player corresponding to URL3 Observe URL3 Source code to find the corresponding player basic information and game data and filter storage

Actually, reptiles are just html On the operation , and html Its structure is very simple, there is only one , It's a big box for a small one , The small frame is covered with a small frame , Such layers of nesting .

The goal is URL as follows :

  • URL1:http://nba.hupu.com/players/
  • URL2( Take the Laker team as an example ):https://nba.hupu.com/players/lakers
  • URL3( Take James for example ):https://nba.hupu.com/players/lebronjames-650.html

First reference the module

from bs4 import BeautifulSoup
import requests
import xlsxwriter
import os

see URL1 Source code , You can see the team name and its corresponding URL2 stay span In the label <span class><a href = “..."> Next , And then find its parent box and grandfather box , The following ideas are the same , The graph is as follows :


here , Can pass requests Module and bs4 Modules are indexed purposefully , Get a list of team names .

def Teamlists(url):
    lables=soup.select('html body div div div ul li span a') 
    for lable in lables:
    teamname=input(" Please enter the name of the team you want to query :")# Here it can be changed to GUI Key values in the interface
    for item in lables:
    return URL2

So we got the team's URL2, Then observe URL2 The content of the web page , You can see the name of the player in the label a in <a target = "_blank" href = ....> Next , At the same time, it also stores the corresponding player's URL3, Here's the picture :

here , So it's still through requests Module and bs4 Modules are indexed accordingly , Get a list of player names and the corresponding URL3.

# User defined function to get the list of team members and the corresponding URL
def playerlists(URL2):
    lables2=soup2.select('html body div div table tbody tr td b a')
    for lable2 in lables2:
    name=input(" Please enter player name :") # Here it can be changed to GUI Key values in the interface
    for item2 in lables2:
    return URL3,name

Now you've got the team's URL3, Then observe URL3 The content of the web page , You can see the player's basic information in the label p Next , Players' regular season career data and playoff career data are in the label td Next , Here's the picture :

Again , Still pass requests Module and bs4 Modules are indexed accordingly , Get the player's basic information and career data , And for the player's regular season and playoff career data will be screened and stored , obtain data list .

def Competition(URL3):
    lables3=soup3.select('html body div div div div div div div div p')
    lables4=soup3.select('div div table tbody tr td')
    for lable3 in lables3:
     print(introduction)  # Basic player information
    for lable4 in lables4:
    for i in range(len(data)):
        if data[i]==' Career regular season averages ':
    for x in range(len(data)):
        if data[x]==' Career playoff averages ':
    return data

Through the above crawler, we get the following data , While providing visual data Easy to bind after GUI Interface key events

  • obtain NBA Standard names for all teams in ;
  • Get the standard names of all players in the team through a designated team ;
  • Get the corresponding basic information and regular season and playoff data through designated players ;

   Visualization part

Ideas : Create folder   Create tables and line charts

Custom functions create tables , Application os Module to write , Return to the path of the created folder , The code is as follows :

def file_add(path):  # The internal function at this point path But with GUI Interface Statictext binding
     if not os.path.isdir(creatpath):
     print(" Folder exists ")
    return creatpath

Application xlsxwriter Modules in creatpath Under the path Custom function creation excel Tables put data and construct line graphs at the same time , The code is as follows :

def player_chart(name,data,creatpath):
    # This is the table name —— Player name +chart
    worksheet.write_row('A1',headings,bold) # Write header
    for i in range(num):
        worksheet.write_row('A'+str(i+1),data[a:c]) # Write data
    chart_col = EXCEL.add_chart({'type': 'line'}) # Create a line chart
        'name': '='+name+'!$R$1', # Set the broken line description name
        'categories':'='+name+'!$A$2:$A$'+str(num), # Set chart category label range
        'values': '='+name+'!$R$2:$R$'+str(num-1),    # Set chart data range
        'line': {'color': 'red'}, })   # Set chart line properties
    # Set the title of the icon and want to x,y Axis information
    chart_col.set_title({'name': name+' Career average regular season scores '}) 
    chart_col.set_x_axis({'name': ' year  ( year )'}) 
    chart_col.set_y_axis({'name': ' Average score ( branch )'})
    chart_col.set_style(1) # Set chart style
    worksheet.insert_chart('A14', chart_col, {'x_offset':25, 'y_offset':3,}) # Insert the icon into the workbench and set the offset

Data table effect display , Take James as an example

And turn on auto generated Excel, The corresponding line chart is displayed directly , There's no need to rearrange !

Now combine task one's crawler with task two's data visualization , Can get real-time player regular season data and playoff data summary , There's also a real-time line chart of players' careers .


Be careful : If you're looking for python Well paid jobs . I suggest you write more about real enterprise projects and accumulate experience . Or you won't find a job , Of course, a lot of people have never been in a business , How can there be project experience ? So you have to find more enterprise projects and practice more . If you're lazy and don't want to find , You can also enter my Python Circle of communication :1156465813. There are some real enterprise project cases that I have written before in the group file . You can take it to study , If you don't understand, you can find me in your skirt , I'll answer you patiently when I have time .


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