Try it out in a PowerShell Jupyter Notebook here:
A suite of command-line tools for working with PowerShell arrays.
Function |
---|
ConvertFrom-FixedData |
ConvertFrom-SQLToPS |
ConvertFrom-SSV |
ConvertFrom-TranspileSQL |
Convert-IntoCSV |
ConvertTo-Property |
Get-DataInfo |
GetDataTypePrecedence |
Get-DateRange |
Get-PropertyName |
Get-PropertyStats |
Group-ByAndMeasure |
Import-SSV |
Invoke-ScanProperties |
Invoke-TranspileSQL |
New-DataFrame |
New-LookupTable |
This function prints information about a PowerShell object array including the column name, column data type, non-null values.
$data = ConvertFrom-Csv @"
Region,ItemName,Units,TotalSold
,screws,5.3,3
North,,5.7,58
East,drill,6.3
"@
$data.info()
# Get-DataInfo $data
Entries: 3
Columns: 4
ColumnName NonNull DataType
---------- ------- --------
Region 2 string
ItemName 2 string
Units 3 double
TotalSold 2 int
string(2) double(1) int(1)
Read comma-separated values (csv). $target can be a URL, a file, or a string
#$file = "targetData.csv"
$url = 'https://raw.githubusercontent.com/dfinke/ImportExcel/master/Examples/JustCharts/TargetData.csv'
$str = @"
"Cost","Date","Name"
"1.1","1/1/2015","John"
"2.1","1/2/2015","Tom"
"5.1","1/2/2015","Dick"
"11.1","1/2/2015","Harry"
"7.1","1/2/2015","Jane"
"22.1","1/2/2015","Mary"
"32.1","1/2/2015","Liz"
"@
$str, $url | Read-Csv
Cost Date Name
---- ---- ----
1.1 1/1/2015 John
2.1 1/2/2015 Tom
5.1 1/2/2015 Dick
11.1 1/2/2015 Harry
7.1 1/2/2015 Jane
22.1 1/2/2015 Mary
32.1 1/2/2015 Liz
1.1 1/1/2015 John
2.1 1/2/2015 Tom
5.1 1/2/2015 Dick
11.1 1/2/2015 Harry
7.1 1/2/2015 Jane
22.1 1/2/2015 Mary
32.1 1/2/2015 Liz
Creates an array of objects, size-mutable, can be heterogeneous, tabular data
New-DataFrame (Get-DateRange 1/1 -periods 5) p1,p2,3 {Get-Random}
Index p1 p2 3
----- -- -- -
2020-01-01 708420917 1112428663 523426202
2020-01-02 1643869654 2086787197 1127195815
2020-01-03 1095068483 2006354687 1612194161
2020-01-04 1561123134 1004618008 1431794170
2020-01-05 851611997 189055864 871342612
Groups data and can either get the Count, Average, Sum, Maximum or Minimum
$str = @"
Region,Item,TotalSold
West,apple,2
South,lemon,4
East,avocado,12
South,screwdriver,70
North,avocado,59
North,hammer,33
North,screws,69
East,apple,21
West,lemon,67
South,drill,52
"@
Group-ByAndMeasure (Read-Csv $str) Region TotalSold Sum
Region Sum
------ ---
West 69
South 126
East 33
North 161
Return a fixed frequency Datetime Index
Get-DateRange 1/1/2020 -periods 6
2020-01-01
2020-01-02
2020-01-03
2020-01-04
2020-01-05
2020-01-06
New-DataFrame (Get-DateRange 1/1/2020 -periods 3 -freq M) a,b,c
Index a b c
----- - - -
2020-01-01 [missing] [missing] [missing]
2020-02-01 [missing] [missing] [missing]
2020-03-01 [missing] [missing] [missing]
The PSKit
module adds a method Query()
to lists of objects. You pass a SQL statement to it to work on that set of data. Currently, the SQL syntax is limited to Select the properties you want to see and a Where clause with value type comparison and logical operators. It does not support multiple arrays, joins or aliasing etc.
$data = ConvertFrom-Csv @"
name,age,cash
Chris,44,72
Brian,26,110
Ryan,18,145
Joe,34,83
"@
$data = ConvertFrom-Csv @"
name,phoneNumber
Chris,555-999-1111
Brian,555-123-4567
Ryan,555-123-8901
Joe,555-777-1111
Jane,555-777-2222
"@
Find phone numbers matching the pattern "ddd–123-dddd".
PS C:\ $data.ScanProperties("\d{3}-123-\d{4}")
name phoneNumber
---- -----------
Brian 555-123-4567
Ryan 555-123-8901
Find records that end in "an$".
PS C:\ $data.ScanProperties("an$")
name phoneNumber
---- -----------
Brian 555-123-4567
Ryan 555-123-8901
PS C:\ (Get-Service).ScanProperties("^mssql")
Status Name DisplayName ServicesDependedOn
------ ---- ----------- ------------------
Stopped MSSQLSERVER SQL Server (MSSQLSERVER) {}
Stopped MSSQLSERVER SQL Server (MSSQLSERVER) {}
Stopped SQLSERVERAGENT SQL Server Agent (MSSQLSERVER) {MSSQLSERVER}
Stopped SQLSERVERAGENT SQL Server Agent (MSSQLSERVER) {MSSQLSERVER}
Note: This feature requires the PowerShell module PSStringScanner.
Install-Module PSStringScanner
Supports a simple SQL Select statement syntax for querying arrays of data.
$actual = $data.query("SELECT cash, name FROM data where name like '*i*' and cash > 100")
cash name
---- ----
72 Chris
110 Brian
Get-PropertyStats
will calculate different statistics based on the type of each column.
Note: There are two other ways to get the same results $data | Get-PropertyStats
or $data.stats()
$data = ConvertFrom-Csv @"
a,b,c,d,e,f,g
2,0.0,FALSE,"""Yes!""",2011-11-11 11:00,2012-09-08,12:34
42,3.1415,TRUE,"Oh, good",2014-09-15,12/6/70,0:07 PM
66,,False,2198,,,
"@
Get-PropertyStats $data
ColumnName DataType HasNulls Min Max Median StandardDeviation Variance Sum
---------- -------- -------- --- --- ------ ----------------- -------- ---
a int False 2 66 42 32.331615074619 1045.33333333333 110
b double True 0 3.1415 0 1.81374587065921 3.28967408333333 3.1415
c bool False
d string False
e datetime True
f datetime True
g datetime True
Have data that with a unique id column? Want to use it as a lookup table? Here you go:
$data = ConvertFrom-Csv @"
slug,place,latitude,longitude
dcl,Downtown Coffee Lounge,32.35066,-95.30181
tyler-museum,Tyler Museum of Art,32.33396,-95.28174
genecov,Genecov Sculpture,32.299076986939205,-95.31571447849274
"@
This is similar to Group-Object
built into PowerShell
. New-LookupTable also handles missing data.
PS C:\> New-LookupTable $data slug
Name Value
---- -----
dcl @{slug=dcl; place=Downtown Coffee Lounge; latitude=32.35066; longitude=-95.30181}
tyler-museum @{slug=tyler-museum; place=Tyler Museum of Art; latitude=32.33396; longitude=-95.28174}
genecov @{slug=genecov; place=Genecov Sculpture; latitude=32.299076986939205; longitude=-95.3157144...
Fixed-width files are particularly challenging to parse. Save yourself some frustration by using a CSV-formatted schema to convert your fixed-width file into PowerShell objects.
Chris44 72
Brian26110
Ryan 18145
Joe 34 83
column,start,length
name,1,5
age,6,2
cash,8,3
The function that parses the data.
ConvertFrom-FixedData -fixedData (Get-Content .\fixedData.txt) -schema (Import-Csv .\fixedDataSchema.csv)
name age cash
---- --- ----
Chris 44 72
Brian 26 110
Ryan 18 145
Joe 34 83