In the era of big data, the sources of data are diverse and complex.
For the huge amount of data with various channels and formats, data cleaning has become a rigid need.
In data analysis, data cleaning is actually a very heavy and critical step.
As a data cleaning tool, Power Query can centralize and uniformly convert these multi-source data into the required format, creating prerequisites for data analysis.
In addition, Power Query can also make office automation a step further. It seamlessly connects with the commonly used office software Excel, automates daily repetitive work, and obtains efficient and accurate processing results. It can not only save labor costs for enterprises, but also save labor costs for individuals. time.
Before using Power Query, the author of the book "Power Query Combat: Intensive Application of Excel Intelligent Data Cleaning Artifact" used the functions in Excel, but since using Power Query, many seemingly difficult operations in Excel It can be completed by simple processing, and you don't even need to write functions yourself, you can directly operate in the operation interface.
For those without programming experience, the key to using Power Query is to figure out the format of the data. If you understand this, it will be much easier to use the function.
There are as many as hundreds of functions in Power Query. Selecting the commonly used functions introduced in the case and using them proficiently can basically solve most of the problems encountered in the work.
This book not only explains the operation process, but also helps readers expand their thinking, so that readers can draw inferences to solve problems; at the same time, it explains the calculation process of functions in detail through rich cases, so that readers can better understand the calculation process of functions. The calculation logic of the function is clearer.
Office workers who often use Excel
People who often need to integrate data from various channels
Statisticians who often need to generate different reports
Business operations management and analysts
statistician doing market analysis
Others who are interested in data collation and analysis
Chapter 1: Mainly introduces some basic concepts of Power Query, such as the function of Power Query, opening method, main interface function, data type, function overview, basic syntax, data reference method, etc.
Chapter 2: Introduces the method of importing data from various data sources in Power Query, such as importing data from Excel workbooks, worksheets, tables, text files, folders, MySQL databases, Web pages and other data sources.
Chapter 3: Taking the self-made file manager as a case, familiarize yourself with some basic operations through data acquisition, extraction, judgment, and screening, and finally use batch files to move, copy, delete, and rename files in batches.
Chapter 4: Comparing the conditional calculation formulas in Excel, understand the data automatic cleaning calculation function in Power Query.
Chapter 5: Compare the data deduplication and data matching functions in Excel, and understand the implementation method of the VLOOKUP matching function in Power Query.
Chapter 6: Comparing the methods of extracting data in text in Excel, understand the more powerful extraction methods in Power Query, including extracting arbitrary numbers, English, symbols, and characters of specified national languages.
Chapter 7: Compare absolute references and relative references in Excel, and learn how to implement relative references, absolute references, and mixed references in Power Query.
Chapter 8: Taking the batch upload of product data tables on the e-commerce platform as a case, by analyzing the format of the target table, it introduces how to use Power Query to clean the source data table and meet the requirements of the target table format, and how to deal with the title content and the order of columns Forms that do not meet the requirements.
Chapter 9: Taking the out-of-stock and replenishment of inventory as an example, the data is cleaned through Power Query, so that it can automatically display the out-of-stock situation and the need for replenishment.
Chapter 10: Compared with the "Split Columns" function in Excel, the rules of the "Split Columns" function in Power Query are diverse. It can not only split columns by separator, number of characters, and position, but also by There are rules to convert split columns, and custom rules to convert split columns (such as Chinese to English, English to numbers, etc.).
Chapter 11: Use Power Query to process the data of the merged cells to make it available for analysis, including the merging of column headers, row headers, and data values, etc.
Chapter 12: Mainly introduces the application of time functions in Power Query, the main classification of date and time functions, the mutual conversion of date formats, etc., and fully demonstrates the application of time functions by taking shift schedules and account period calculations as examples.
Chapter 13: mainly introduces how to extract web page data with table tags, how to clean the data in JSON format, and how to extract specified data in the code.
Chapter 14: Mainly introduces the concept of functions in Power Query, notes on custom functions, and actual combat of custom functions.
Chapter 15: Using Power Query for artificial intelligence development, by interpreting the instructions in open documents and connecting to open APIs, data processing is made more intelligent.
