Analyzing PG&E data with VisiData [wiki.dlma]

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====== Analyzing PG&E data with VisiData ======

At the PG&E website, you can download a CSV table of your energy usage. Click "Energy Usage Details" and then the "Green Button" at their site to download your data.

{{:general:vd-pge-green-button.png?direct|}}

PG&E CSVs come with 5 rows of metadata followed by ''Type'', ''Date'', ''Start Time'', ''End Time'', ''Usage'', ''Units'', ''Cost'', ''Notes'' columns. Delete the five rows of metadata in a text editor, or use ''tail'' to remove them like so (or with ''tail -n +6'' for older tail):

    tail +6 pge_electric_interval_data.csv | vd -f csv -

Then prepare your PG&E data like so:

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

^ Key ^ Meaning ^
| - | Hide columns TYPE, END TIME, UNITS and NOTES |
| = | Create a new column for weekday. Enter "DATE.weekday()" |
| = | Create a new column for weekday name. Enter "DATE.strftime('%A')" |
| %%^%% | Rename "START TIME" to one word since column names should be one word for Python expressions. |
| C | Go to column mode and... |
| t | Select the DATE and START TIME columns |
| & | Make a new column that merges them |
| - | (Optionally delete some columns' rows from column mode to really delete columns from the sheet.) |
| q, - | Quit the Column mode, hide (sets their width to 0) DATE and START TIME columns |
| O | Go to options mode and... |
| e | Set ''disp_date_fmt'' to ''%Y-%m-%d %H:%M'' (or do it in column mode's ''fmtstr'' for the one column.) |
| q | Quit options mode. |
| @!, %, $ | Set DATE_START_TIME to date format and important, USAGE to float, COST to currency |
| = | Add a column, enter ''COST/USAGE'', (Make it float with ''%'') |
| %%^%% | Rename COST/USAGE to ''kWh rate'' |
| H,V and _ | Move and resize the columns. |

You should end up with a sheet with usable data. Note that ''@'' means "date format", ''#'' means "integer", ''%'' means "float" and ''$'' means "currency". Also note that we haven't set aggregator types yet. We'll use those for frequency tables.

{{:general:vd-pge-data-ready.png?direct|}}

===== View average usage by hour of day =====

^ Key ^ Meaning ^
| - | Hide all columns, leaving only ''time'', ''USAGE'', and ''COST'' |
| + | On ''USAGE'' and ''COST'', set aggregator type to... say, ''avg'' for average. |
| F | On the ''time'' column, tap ''F'' to get a frequency table. |
| [ | The frequency table is sorted on the new aggregations, on ''time'' column, use ''['' to sort by time again. |
| - | Remove the new ''count'' column. |
| C, e, "%H:%M", q, @! | Go to column mode, set ''time'' column format to ''%H:%M'', exit column mode, set ''time'' to date format. |
| g. | Display a graph with all visible columns. |
| -, + | Zoom in and out of the graph. |
| q, q | Quit the graph, quit the frequency sheet |
| C, t, ge, 8 | Column mode, toggle ''date_time'', ''DATE'', ''wday_num'', ''wday'', edit width to 8, to see these columns again. |

{{:general:vd-pge-graph-by-hour-of-day.png?direct|}}

===== View average usage by day of week =====

^ Key ^ Meaning ^
| - | Hide all columns, leaving only ''wday_num'', ''time'', ''USAGE'', and ''COST'' |
| C, t, & | Column mode, toggle ''wday_num'', ''time'', make a new column that joins them. |
| = | With ''TIME'' as string format, make a new row as ''int(int(TIME[:2])/4)*4'' |

===== Select Rows to Analyze =====

Directly selecting ranges of rows:

^ Key ^ Meaning ^
| s,t,u | Select/toggle/unselect current row. |
| , | Select all rows matching value of current cell |
| gs,gt,gu | ... all rows |
| zs,zt,zu | ... from top to cursor |
| gzs,gzt,gzu | ... from cursor to bottom (Or... ''zs,gt'', one less thing to remember) |
| " | Open duplicate sheet with only selected rows. |

Select based on a pattern:

^ Key ^ Meaning ^
| %%|%% | On DATE_START_TIME column, select by regex, like "-11-" for November |
| %%z|%% | Select rows matching Python expr "DATE_START_TIME [-3:] == '-07'" |
| " | To open a new sheet with just those selected rows. |


===== Visualize Data =====

^ Key ^ Meaning ^
| . or g. | Select columns to graph them. Notice rate changes. Notice times of high use. |
| +, - | Navigate with hjkl, zoom in and out ([[https://www.visidata.org/docs/graph/|more]]) |

====== Further Resources ======

I have another tutorial at [[vd]] that merges/joins three CSV tables.