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Tableau generally works best when input data is in 'normalized' format, rather than cross-tab. This is also referred to as converting from 'wide format' to 'long format'.
That is, converting from:
To:
Tableau provides a 'reshaping tool' for Excel users, but if you don't have Excel, you're stuck.
So how can you get a spreadsheet into this format, without using Excel?
Steve BennettSteve Bennett57.7k23 gold badges106 silver badges143 bronze badges
3 Answers
Well, you can use this handy Google Sheets script I made.
Full write-up with instructions on how to install.
Steve BennettSteve Bennett57.7k23 gold badges106 silver badges143 bronze badges
Newer versions of Tableau (9.0 and above) allow reshaping of data on import. It's as simple as selecting the columns you want to stack. Here's a useful tutorial.
In 2018, Tableau released Tableau Prep for reshaping and wrangling Data for analysis.
Some commercial tools useful for reshaping and cleaning data worth investigating are:
Trifacta was created by some of the people who worked on the previous academic DataWrangler project. I've been told that Alteryx is good for some prep tasks for geospatial related data, and have met some enthusiastic Paxata users.
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I have too little hands on experience with them to give more than a reference to their web sites, tending to use Python scripts instead to date.
If you want to 'fold' columns that you want to merge into a single column. Tableau wrote a helpful tutorial here. Tableau 9 introduced some useful reshaping features for unpivoting tables and splitting columns.
Alex Blakemore8,8412 gold badges20 silver badges43 bronze badges
robrocrobroc
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If you are comfortable with command lines and the Unix style of combining small tools using pipes, check out the open source csvkit toolsuite.
You can combine these utilities in many ways to get different effects, so the exact sequence of steps depends on your datasets (that's the point of the tools after all).
But for reshaping tasks, you could use csvcut to pull out columns of interest, csvgrep to pull out rows of interest and cvsstack to combine multiple csv files into one longer one, along with the -g and -n options to add a grouping field.
There are several other useful commands, and if you are familiar with Unix or linux, you can figure out what they do quickly just from the command names. Picture editing tool for windows 10.
Alex BlakemoreAlex Blakemore8,8412 gold badges20 silver badges43 bronze badges
Tableau For Mac Download
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Tableau Reshaping Tool
Tableau significantly prefers long and lean data to bulky wide data. To translate the data that Qualtrics exports to data better suited for insights, there are three functions in the QualtricsTools package here to help.
(If you're using Insights, use
headerrows=3
. If you're using legacy data, use headerrows=2
).Here we demonstrate two different ways to write the output, into CSV files and into a single XLS file using respectively the data.table package's fwrite function and the WriteXLS package. Flashair software.This outputs a workbook with three sheets:
The three functions designed specifically to help with this reshaping process are
lean_responses()
, create_response_column_dictionary()
, and create_panel_data()
.lean_responses()
requires two parameters, question_blocks
and survey_responses
.The question_blocks
parameter is a list of blocks with questions inserted in place of the block elements' names. This is most easily created by using the get_setup()
function and using the blocks
variable that it outputs to the global scope. The survey_responses
parameter is more straightforward -- it's just the responses
data frame as imported by ask_for_csv()
. The output of the function is a data frame with a single response in each row. Each row contains a respondent ID, the response column, the raw response, and the coded response.Tableu Reshaping Tool For Machine
create_response_column_dictionary()
requires two parameters, question_blocks
and orig_first_row
. The question_blocks
refers to the same parameter that was given to lean_responses()
above. The orig_first_row
refers to a data frame with only one row: the first row of the response CSV with headers. The get_setup()
function provides both a blocks
variable and an original_first_row
variable to the global scope that can be used as the question_blocks
and orig_first_row
parameters respectively. The output of the function is a data frame with each response column in a unique row. Each row contains the data export tag of the question the response column corresponds to, the question stem and question choice, the question types, and the response type.create_panel_data()
requires one parameter and optionally takes an additional three. The first (required) parameter is a list of response column names to be included in the panel data. The next three are the survey_responses
, the lean_responses
and the question_dict
. The survey_responses
are the responses as a data frame as imported by the ask_for_csv()
function, or as provided by the get_setup()
function. The lean_responses
parameter is a data frame created using the lean_responses()
function. The question_dict
parameter is a question dictionary created using the create_response_column_dictionary()
function. The output is a data frame with each respondent in a row, and each specified panel data column included either verbatim from the response set, or as raw and coded responses included from the lean_responses
data frame.Reshaping Tool For Photos
The data is split into three different outputs to decrease the amount of repetition. Of course, you can create only one, or two, or all three of these data frames, depending on your needs.
I hope this helps.