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DoTERRA with Melissa Group

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Anthony Cruz
Anthony Cruz

Shark-Export (1).csv !!HOT!!

You can export data to a comma-separated values (.csv) file or (.pdf) document, and use the exported data to build reports. For example, if there are 10 critical events that have not been resolved, you can export the data from the Event Management inventory page to create a report, and then take appropriate action.

Shark-Export (1).csv

As a last resort, you can also build the import file manually by collecting the necessary data and creating a CSV file. This file can be created as a simple text file and saved with the .csv extension, or you can use a spreadsheet program such as Excel.

You could rustle up a script to turn that into CSV, but it'd be simpler if you just create a schema file for this fixed format which defines where the fields you expect start and end. Like this is one, schema.csv:

The csvsql command does the opposite of sql2csv by letting CSV data be loaded into an SQL database. It generates the CREATE TABLE command needed to store the contents of a CSV file. If we take that CSV data we just generated and stored it in a file films.csv, then we can run csvsql like so:

Our first stop is the csvclean command. We've got to this point extracting data from various databases but often you may be faced with a CSV file of, shall we say dubious, quality. With csvclean you can separate out the rows with syntax errors or incorrect numbers of values. csvclean filename.csv will put the good rows into filename_out.csv and the bad rows and related errors into filename_err.csv. Add -n and the command will dry-run just telling you where the errors are.

If you don't give these commands a filename to work with they default to using STDIN, which makes it easy to string them together in classic Unix style. In a more SQL vein, there's CSVkit's csvjoin, capable of doing a join operation on a number of CSV files so given two files such as country.csv:

The last two commands are useful for all CSV file users. Getting a well formatted print of a CSV file can be a chore but csvlook will take care of that for you. Working out what's in your CSV file is a journey which can begin with a good set of statistics which is where csvstat comes in. It will do useful analysis of each field in the CSV file you hand it. Here's a snippet from it running on our films.csv file:

Remember to choose File, Save as to get an analysis document to study. This output may be converted to a spreadsheet file, by using the File, Export, File, Save as selection sequence, and choosing .csv as the required file format.

Use the data set ponds.csv for this example (see the instructions on acquiring data files). This is the same data set used for Exercise 1B, revisit that exercise for details on this hypothetical data set. Read in and plot the data:

In this script, we use the Import-CSV cmdlet, which knows how to read .CSV-formatted files. We tell the Import-CSV cmdlet that each row of the CSV data located in C:\powershell called users.csv contains information in three columns: The Name of the user; the samAccountName of the user, which is basically the login ID for the user; and the organizational unit (OU) of Active Directory that the user needs to live in.

So far, this tutorial has only dealt with one type of data: a spreadsheet,which we use in .csv (comma separated variable) file format. This format issuitable for plotting data in the form of points or locations, but if you wantto show data on a per-region basis (such as life expectancy per country), theeasiest way to do so is to use an ESRI shapefile.

You may have to delete and re-upload your table to make the changes takeeffect, in which case you should make your changes in the original spreadsheet,save that spreadsheet as a .csv file (or whatever format was originally used),and upload it just as you did before. 041b061a72


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