VisiData [wiki.dlma]

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====== VisiData ======

**[[https://www.visidata.org/|VisiData]]** is an interactive CLI table explorer with vim key bindings. Here is [[https://jsvine.github.io/intro-to-visidata/index.html|a really great tutorial]]. These are notes to myself.

====== Source Table Recommendations ======

Gather data with more granularity than you think you need. You often need three tables:

  - **Logs**: Include date, build (includes platform ID), product ID, params of log, total count, unique devices.
  - **Device Activity**: Includes date, build, product ID, active time, active device count.
  - **Mappings from product ID to product name**: (Maybe from platform ID or from product ID.)

====== Open VisiData and Set Data Types ======

  $ vd logs.csv active_devices.csv id_name.csv

===== Set Column Types, Widths, Names, Importance =====

^ Key ^ Meaning ^
| _ | Adjust widths of columns |
| @ | Column type is date. |
| ! | Column is important. (Will be key for table merging.) |
| # | Column is integer. (Set aggregator to sum.) |
| + | Set aggregator, usually to "sum" |
| ; | Extract regex to new column. Ex, ''(video|audio)'', ''(^..)'' or ''(^([STUVW]%%...%%|..))'' |
| %%^%% | rename the column. Might have to be "product_id" or "platform_id" |
| = | Use Python function to create new column. Ex, hex to dec: ''int(curcol,16)'' |
| : | Split column by regex |
| - | Hide column |
| S | Go to "Sheets" sheet, to select another sheet to format. |
| q | Leave the sheet. (''gq'' quit all sheets) |
| F | Make a Frequency Table for the selected column. (''gF'' for selected columns) |
| U | Undo. ''R'' Redo. |
| d | Delete row. (I only use this on Sheets sheet.) |
| , | Select all rows that match this column's value |
| " | Open duplicate sheet with only selected rows |

===== Inspecting Columnar Data =====

^ Key ^ Meaning ^
| I | Describe all columns, errors, distinct, mode, mean, median, stdev, etc. |
| i | Add a column of incrementing numbers (useful for '.' charts) |
| . | Requires an "important" numeric column for row data. Make chart. |
| O | Options to enable "numeric_binning" and set number of "histogram_bins" (use 'e') |
| F | Frequency table of row counts, or histogram if numeric_binning is true |

Calculating a percentage-of-total column for a numeric column:

^ Key ^ Meaning ^
| # | Set column type to "int". |
| I | Describe all columns. (Highlight the "sum" cell for the column of interest.) |
| ~ | Convert that column to "text" so it'll be copied correctly for pasting later. |
| zy | Yank the value of the sum. |
| q | Quit the Describe sheet. |
| = | New column. Enter ''curcol/'', use Ctrl+y to paste the column sum value. |
====== Case Study Link: Exported CSV from PG&E ======

Visit [[vd-pge]].

====== Cast Study: Merging Two Tables, logs and metadata ======

==== Protip: Use column view to set multiple columns at once ====

^ Key ^ Meaning ^
| C | Go to column view, each row is data for a column. |
| t | Select rows, select all integer rows. |
| ge | Go to "type" column, enter ''ge'' (global edit), type "int" |
|    | Go to "aggregators", enter ''ge'', type "sum" |
| q | Leave that table. |

For example, your "logs.csv" would end up looking like:

{{:general:logs.png?direct|}}

Your active_devices.csv would look like this:

{{:general:active_devices.png?direct|}}

====== Join Sheets ======

Use ''!'' to set Key columns. Use ''F'' (or ''gF'') to remove dupes of Keys by making a Frequency Table.

^ Key ^ Meaning ^
|   | The key columns to join have to match names. Check and rename with ''^''. |
| S | Go to Sheets sheet |
| t | (toggle) Select the sheets you want to join by key columns. |
| & | (or g&) Join sheets. Type "inner" for an inner join. |
| gu | Next time you're in Sheets, "global unselect" to unselect the sheets you selected. |

==== Protip: Remove insignificant noisy rows ====

^ Key ^ Meaning ^
| %%z|%% | Select rows matching Python expression. Type "blits > 10000" |
| " | Make a new sheet with selected rows |

And the merge of the logs and active devices sheets would look like:

{{:general:merge_logs_active.png?direct|}}

Do a similar thing to join the Joined Sheet with the product Name sheet.

====== Process Data ======

In your final Joined sheet, add rows that are calculations of other rows.

^ Key ^ Meaning ^
| HL | (JK for rows) Move columns |
| - | Remove columns |
|   | Maybe use ''C'' to assure desired columns are ints and aggregators are "sum" |
| ! | Toggle key columns. |
| gF | global Frequency Table so key columns are unique. |
| = | Add column. Enter ''count_sum * 100 / active_devices_sum'' |
| % | Set new column as float. |
| _ | Resize columns |
| ] | Sort by column |
| . | (''g.'' for multiple columns) Make a graph based on Key column. |

{{:general:joined_sheets_pct.png?direct|}}

Now you should have some basic info to keep exploring. When you want to save what you've done:

^ Key ^ Meaning ^
| Ctrl+s | Save sheet |
| Ctrl+d | Save command log (cmdlog). Use extension ".vd". You can replay what you've done later! |

The commandlog is a CSV file too. The first lines are the open file commands. So to replay, you only have to specify the command log like so:

  $ vd --play=my_cmdlog.vd --replay-wait=0.5

====== Lists in Cells for Frequency Tables ======

Sometimes you want one of the columns in a Frequency Table to be a list of unique values. Let's say the column title is "my_column", then:

^ Key ^ Meaning ^
| + | Set the aggregator to "List" |
| F | Make a Frequency Table for the selected column. (gF for selected columns) |
| =, ','.join(set(my_column)) | Create a new column of a comma delimited Python Set of cell entries. |