By Jacqueline Kazil
How do you are taking your info research abilities past Excel to the following point? through studying simply enough Python to get stuff performed. This hands-on consultant indicates non-programmers such as you the best way to strategy details that is in the beginning too messy or tricky to entry. you do not need to grasp something concerning the Python programming language to start. via numerous step by step workouts, you are going to the way to gather, fresh, research, and current info successfully. you will additionally become aware of how you can automate your info procedure, time table dossier- modifying and clean-up initiatives, technique higher datasets, and create compelling tales with information you bought.
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Additional resources for Data Wrangling with Python: Tips and Tools to Make Your Life Easier
Let’s try it out with the string 'cat,dog,horse': dir('cat,dog,horse') For now, ignore everything at the beginning of the returned list (the strings starting with double underscores). These are internal or private methods Python uses. The methods that are most useful are contained in the second part of the returned list output. Many of these methods are obvious, or self-documenting. info | 35 'rsplit', 'rstrip', 'split', 'splitlines', 'startswith', 'strip', 'swapcase', 'title', 'translate', 'upper', 'zfill'] If you look at the string 'cat,dog,horse', it looks like it is a list saved in a string.
This is extremely helpful when you are using a variable to hold data and need to know what type of data is in the variable. Consider the zip code example from earlier in the chapter. Here, we have two different uses for the value 20011. In the first case, it is a zip code stored as a string. In the second case, it is an integer: '20011' 20011 If those values were stored in variables, they would be further obscured and we might not know or remember whether we used a string or an integer. If we pass the value to the built-in method type, then Python will tell us what kind of data type the object is.
For this example, we are using CSV (text only). If you open the file in your text editor,1 you will see data holding rows containing the values in Table 3-1. Table 3-1. 00000 Low no value no value High no value no value Comments no value no value a Bold items are included in the sample data. To make the data easier to read, a sample of the data with trimmed-down fields is shown here. 00000" 1 To complete the exercises in this chapter, you will need a good text editor. If you haven’t already installed one, follow the instructions in “Install a Code Editor” on page 15.