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CSV stands for comma separated values. Those files are still used to transport tabular data between applications that are not directly connected. The files can be edited with any spreadsheet application like Microsoft Excel. | CSV stands for comma separated values. Those files are still used to transport tabular data between applications that are not directly connected. |
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There are some things one need to know about CSV file in order to deal with them: | Such files can be edited with any spreadsheet application like Microsoft Excel. |
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* Fields are separated by commas | There are some things one need to know about CSV files in order to deal with them: * Fields are separated by commas. Well, mostly. |
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* If a field contains either a comma or one of the end line chars, either the char(s) or the whole contents needs to be escaped. Excel escapes these values by embedding the field inside a set of double quotes. For example, a single cell with the text apples, carrots, and oranges becomes "apples, carrots, and oranges" | * If a field contains either a comma or a double quote or one of the end line chars either the char(s) or the whole contents needs to be escaped. |
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For details and background information see http://www.csvreader.com/csv_format.php | Excel escapes these values by embedding the field inside a set of double quotes. For example, a single cell with the text `apples, carrots, and oranges` becomes `"apples, carrots, and oranges"`. |
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Note that the format comes with a nasty built-in-problem: there is no way to recognize a cell as being numeric. Converting cells which only contain a proper number does not help because if you enter a digit with a leading quote, Excel handles this as text but again this cannot be recognized as text in the csv file. The only solution is therefore to make an informed guess. | * Strictly speaking the delimiter is not defined in the specs. Some banks offer downloads with a semicolon used as separator instead of a comma. You might wonder why the name of this format is '''Comma''' Separated Values but anyway. Several versions of Excel do not recognize a semicolon as a separator. |
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== Reading a CSV file == | For details and background information see: |
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. http://www.csvreader.com/csv_format.php Note that the format comes with a nasty built-in-problem: there is no way to recognize a cell as being numeric. Converting cells which only contain a proper number does not help because if you enter a digit with a leading quote, Excel handles this as text but again this cannot be recognized as text in the csv file. The only solution is therefore to make an informed guess. This informed guess can vary from file to file and person to person, so please look at the functions {{{Csv2MatrixWithDyalog}}} and {{{Csv2Numeric}}} below to see if you want to change them before you start using this. == Reading and writing CSV files using APLX == Reading and writing CSV files in APLX is straightforward; You can just use the {{{⎕IMPORT}}} and {{{⎕EXPORT}}} system commands, specifying CSV as the format to use: {{{ ⍝ Reading a CSV file... myVariable←⎕IMPORT 'C:\Users\simon\Desktop\spreadsheet_data.csv' 'csv' ⍝ Writing a CSV file some_data←2 3⍴'APL' 'is' 'fine, very fine' 1 2.2 ¯3 some_data ⎕EXPORT 'C:\Users\simon\Desktop\new_data.csv' 'csv' }}} For another example of reading a CSV file of Google finance data and charting it, see [[CSVandChartingAplx| CSV and charting in APLX ]] == Reading a CSV file using Dyalog APL == |
|
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{{attachment:cvsexcel3.jpg}} | ||numeric|| char || date ||currency ||misc|| || 1 ||1 || 2015-03-24 || 1.23||Yes || || 2 ||Hello || 2015-01-01 || ¯10 || || || 3 || || 1999-12-31 || ||No || || 4 ||More || 2001-02-01 ||123456789.1 ||"Are your sure?" || || ||Less || || || || || 5 ||Much more || 2014-04-03 || 0 ||apples, carrots, and bananas|| |
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=== First Step: Partition The String Being Read From File === |
=== First step: partition the string being read from file === |
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==== APL2 Version ==== | |
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r←{ignoreBetween}PartitionRecordsWithAPL2 string;masked;cr;lf;bool | r←PartitionRecordsWithDyalog string;masked;cr;lf;bool |
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⍝ Note that everything between "ignoreBetween" is ignored. ⍝ This can be used to masked stuff between "" (CSV files), for example. ⎕IO←1 (cr lf)←⎕TC[2 3] ⍝ <CarriageReturn> and <LineFeed> →L01×⍳2=⎕NC'ignoreBetween' ignoreBetween←'' ⍝ establish default L01: →L02×⍳masked←0∊⍴ignoreBetween masked←~masked∨≠\masked←'"'=string ⍝ what is not escaped (between "") L02: →L03×⍳~0∊bool←~(cr,lf)⍷masked/string ⍝ are there any unmasked cr/lf in "string"? bool←(~masked)∨masked\bool ⍝ "insert" the masked string[1+(~bool)/⍳⍴bool]←cr ⍝ convert lf into cr string←bool/string ⍝ remove original cr masked←bool/masked →L04 L03:→L03×⍳1∊bool←lf=masked/string ⍝ Are there any unmasked lf in "string"? (((~masked)∨masked\bool)/string)←cr ⍝ change them to cr L04:r←(cr≠masked/string)⊂masked/string ⍝ use unmasked cr for partitioning |
⎕IO←1 ⋄ ⎕ML←3 (cr lf)←⎕UCS 10 13 ⍝ <CarriageReturn> and <LineFeed> :If 0<+/bool←(cr,lf)⍷string ⍝ are there any cr+lf in "string"? string←(~bool)/string ⍝ Let only the cr survive :EndIf :If 0<+/bool←cr=string ⍝ Are there still any cr's? (bool/string)←lf ⍝ Convert them to lf :EndIf ⍝ In the remaining string, there might be lf's inside text, Those ⍝ need to be masked before we decide where records really start. masked←~{⍵∨≠\⍵}'"'=string ⍝ what is not escaped (between "") :If 1∊bool←lf=masked/string ⍝ are there any unmasked lf in "string"? r←(~masked\bool)⊂string :Else ⍝ so it's a single record r←⊂string :EndIf }}} === Second step: extract the real data === {{{ r←{sep}Csv2MatrixWithDyalog csv;bool;⎕IO ⍝ Convert vector-of-text-vectors "csv" that is assumed to ⍝ come from a *.csv file and which got already partitioned ⍝ into an APL matrix. Takes care of escaped stuff etc. ⍝ "sep" defaults to a comma. ⎕IO←1 ⋄ ⎕ML←3 sep←{2=⎕NC ⍵:⍎⍵ ⋄ ','}'sep' r←(⌽∨\0≠⌽↑∘⍴¨csv)/csv ⍝ remove empty stuff from the end if any r←',',¨r ⍝ Add starting seperator bool←{~{⍵∨≠\⍵}'"'=⍵}¨r ⍝ prepare booleans useful to mask escaped stuff r←r{⎕ML←1 ⋄ ⍺⊂⍨⍵=sep}¨bool{⍺\⍺/⍵}¨r ⍝ partition fields by unmasked commas r←⊃{1↓¨⍵}¨r ⍝ Drop command and transform to a matrix r←{'"'≠1⍴⍵:⍵ ⋄ ¯1↓1↓⍵}¨r ⍝ remove leading and trailing " r←Csv2Numeric r ⍝ Convert numeric cells r←(~'""'∘⍷¨r)/¨r ⍝ double-" into a single one |
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==== Dyalog Version ==== | |
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r←{ignoreBetween}PartitionRecordsWithDyalog string;masked;cr;lf;bool ⍝ Takes a string and partitions records. ⍝ Can deal with Mac/Unix/Windows files. ⍝ For that, CR+LF as well as single LFs are converted into CR. ⍝ CR is then used to partition "string". ⍝ Note that everything between "ignoreBetween" is ignored. ⍝ This can be used to masked stuff between "" (CSV files), for example. ⎕IO←1 ⋄ ⎕ML←3 (cr lf)←⎕TC[2 3] ⍝ <CarriageReturn> and <LineFeed> :If 0=⎕NC'ignoreBetween' ignoreBetween←'' ⍝ establish default :EndIf :If ~masked←0∊⍴ignoreBetween masked←~{⍵∨≠\⍵}'"'=string ⍝ what is not escaped (between "") :EndIf :If 0∊bool←~(cr,lf)⍷masked/string ⍝ are there any unmasked cr/lf in "string"? bool←(~masked)∨masked\bool ⍝ "insert" the masked string[1+{⍵/⍳⍴⍵}~bool]←cr ⍝ convert lf into cr string←bool/string ⍝ remove original cr masked←bool/masked :ElseIf 1∊bool←lf=masked/string ⍝ Are there any unmasked lf in "string"? (((~masked)∨masked\bool)/string)←cr ⍝ change them to cr :EndIf r←(cr≠masked/string)⊂masked/string }}} === Second Step: Extract The Real Data === ==== APL2 Version ==== {{{ r←Csv2MatrixWithAPL2 csv;buffer;⎕IO;isNotEmpty;mask;bool ⍝ Convert vector-of-text-vectors "csv" that is assumed to ⍝ come from a *.csv file and which got already partinioned ⍝ into an APL matrix. Takes care of escaped stuff. ⎕IO←1 r←(⌽∨\0≠⌽↑¨⍴¨r)/r ⍝ remove empty stuff from the end if any mask←~mask∨¨≠\¨mask←'"'=¨r ⍝ what is not escaped (between "") r←⊃(','≠¨mask\¨mask/¨r)⊂¨r ⍝ partition fields by commas r←('"'=¨↑¨r)↓¨r ⍝ remove leading " r←(-'"'=¨↑¨¯1↑¨r)↓¨r ⍝ remove trailing " isNotEmpty←0<↑¨⍴¨r ⍝ remember empty fields bool←,isNotEmpty∧∧/¨r∊¨⊂'0123456789.' ⍝ fields which contains only ... (bool/,r)←⍎¨bool/,r ⍝ Make those numeric }}} ==== Dyalog Version ==== {{{ csv←Csv2MatrixWithDyalog csv;bool;⎕IO ⍝ Convert vector-of-text-vectors "csv" that is assumed to ⍝ come from a *.csv file and which got already partinioned ⍝ into an APL matrix. Takes care of escaped stuff. ⎕IO←⎕ML←1 csv/⍨←⌽∨\0≠⌽⊃∘⍴¨csv ⍝ remove empty stuff from the end if any bool←{~{⍵∨≠\⍵}'"'=⍵}¨csv ⍝ prepare booleans useful to mask escaped stuff csv←↑csv{1↓¨(',',⍺)⊂⍨','=⍵}¨',',¨bool{⍺\⍺/⍵}¨csv ⍝ partition fields by unmasked commas csv←{'"'≠1⍴⍵:⍵ ⋄ ¯1↓1↓⍵}¨csv ⍝ remove leading and trailing " csv←{⊃1⊃v←⎕VFI ⍵:⊃2⊃v ⋄ ⍵}¨csv ⍝ make fields whith appropriate content numeric scalars |
r←{ignore}Csv2Numeric r;buffer ⍝ Transform cells that contain digits into numeric values, BUT: ⍝ * Commas are ignored. ⍝ * "$£€¥" are ignored because the left argument "ignore" defaults to those. ⍝ * Blanks are removed ⍝ Example: ⍝ (¯10 3 4 1234.5 12 1000 '1A')←Csv2Numeric '-10' '3' '4' '123,4.5' '£12' '1E3' '1A' ignore←{0<⎕NC ⍵:⍎⍵ ⋄ '$£€¥'}'ignore' buffer←{0=+/bool←'-'=w←⍵:⍵ ⋄ (bool/w)←'¯' ⋄ w}¨r ⍝ "buffer" is a copy of r with "¯" for "-" r←buffer{(0∊⍴⍵):'' ⋄ ,↑1⊃v←⎕VFI ⍺~' ,',ignore:↑2⊃v ⋄ ⍵}¨r ⍝ make fields with appropriate content numeric |
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Put it all together: | |
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Put it all together (here for the Dyalog version): | |
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r←DealWithCsv filename;data ⍝ Read "filename" which is assumed to be a *.csv file ⍝ and converts it into a matrix |
r←{sep} DealWithCsv filename;data ⍝ Read "filename" which is assumed to be a *.csv file ⍝ and convert it into a matrix sep←{2=⎕NC ⍵:⍎⍵ ⋄ ','}'sep' |
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data←'"'PartitionRecordsWithDyalog data r←Csv2MatrixWithDyalog data |
data←PartitionRecordsWithDyalog data r←sep Csv2MatrixWithDyalog data |
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== Writing a CSV file == |
== Writing a CSV file using Dyalog APL == |
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APL is fine, very fine 1 2.2 ¯3 |
APL is fine, very fine 1 2.2 ¯3 |
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The following functions take such an array as right argument and convert it into a string that can be written to a file with the extension ".csv". The left argument defaults to "windows" and can be "unix" or "mac" as well. Note that the left argument is case sensitive. The left argument is used to determine the appropriate record separator. === APL2 Version === (Volunteers needed) === Dyalog Version === |
The following function takes such an array as right argument and converts it into a string that can be written to a file with the extension ".csv". The left argument defaults to "windows" and can be "unix" or "mac" as well. Note that the left argument is case sensitive. The left argument is used to determine the appropriate record separator. |
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r←{os}Array2CsvWithDyalog array;cr;lf;sep;bool;IsChar | r←{os}Array2CsvWithDyalog array;cr;lf;sep;bool;IsChar;dq |
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bool←,(lf∊¨array)∨','∊¨array ⍝ where are special chars used? | dq←,'"'∊¨array ⍝ Where are double quotes in the text? (dq/,array)←{b←'"'=w←⍵ ⋄ (b/w)←⊂'""' ⋄ ⊃,/w}¨dq/,array ⍝ Double the double quotes bool←dq∨,(lf∊¨array)∨','∊¨array ⍝ where are special chars used? |
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bool←'"'∊¨array ⍝ where are special chars used? | |
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((r='¯')/r)←'-' ⍝ Handle ¯ | ((r='¯')/r)←'-' |
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#.Array2Csv 2 3⍴'APL' 'is' 'fine, very fine' 1 2.2 ¯3 APL,is,"fine, very fine" 1,2.2,-3 |
#.Array2CsvWithDyalog 2 3⍴'APL' 'really "really" is' 'fine, very fine' 1 2.2 ¯3 APL,"really ""really"" is","fine, very fine" 1,2.2,-3 |
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|| Update -- KaiJaeger <<DateTime(2012-08-05T11:06:46Z)>> incorporating a couple of findings/suggestions from EllisMorgan.|| || Update -- KaiJaeger <<DateTime(2015-03-24T11:26:39Z)>> bug fix: empty cells were not handled correctly.|| ---- CategoryArticles |
CSV to APL
Contents
CSV stands for comma separated values. Those files are still used to transport tabular data between applications that are not directly connected.
Such files can be edited with any spreadsheet application like Microsoft Excel.
There are some things one need to know about CSV files in order to deal with them:
- Fields are separated by commas. Well, mostly.
- Records are separated with system end of line characters, CRLF (ASCII 13 Dec or 0D Hex and ASCII 10 Dec or 0A Hex respectively) for Windows, LF for Unix, and CR for Mac
- If a field contains either a comma or a double quote or one of the end line chars either the char(s) or the whole contents needs to be escaped.
Excel escapes these values by embedding the field inside a set of double quotes. For example, a single cell with the text apples, carrots, and oranges becomes "apples, carrots, and oranges".
Strictly speaking the delimiter is not defined in the specs. Some banks offer downloads with a semicolon used as separator instead of a comma. You might wonder why the name of this format is Comma Separated Values but anyway. Several versions of Excel do not recognize a semicolon as a separator.
For details and background information see:
Note that the format comes with a nasty built-in-problem: there is no way to recognize a cell as being numeric. Converting cells which only contain a proper number does not help because if you enter a digit with a leading quote, Excel handles this as text but again this cannot be recognized as text in the csv file.
The only solution is therefore to make an informed guess. This informed guess can vary from file to file and person to person, so please look at the functions Csv2MatrixWithDyalog and Csv2Numeric below to see if you want to change them before you start using this.
Reading and writing CSV files using APLX
Reading and writing CSV files in APLX is straightforward; You can just use the ⎕IMPORT and ⎕EXPORT system commands, specifying CSV as the format to use:
⍝ Reading a CSV file... myVariable←⎕IMPORT 'C:\Users\simon\Desktop\spreadsheet_data.csv' 'csv' ⍝ Writing a CSV file some_data←2 3⍴'APL' 'is' 'fine, very fine' 1 2.2 ¯3 some_data ⎕EXPORT 'C:\Users\simon\Desktop\new_data.csv' 'csv'
For another example of reading a CSV file of Google finance data and charting it, see CSV and charting in APLX
Reading a CSV file using Dyalog APL
Given an Excel spreadsheet that looks like this:
numeric |
char |
date |
currency |
misc |
1 |
1 |
2015-03-24 |
1.23 |
Yes |
2 |
Hello |
2015-01-01 |
¯10 |
|
3 |
|
1999-12-31 |
|
No |
4 |
More |
2001-02-01 |
123456789.1 |
"Are your sure?" |
|
Less |
|
|
|
5 |
Much more |
2014-04-03 |
0 |
apples, carrots, and bananas |
Saving this into a csv file, the file can be read into APL. The variable would look like this:
To convert this into an APL matrix is a two-step-process:
- partition the simple string from file
- extract the data and build up the APL matrix
First step: partition the string being read from file
With the following two functions this variable can be transformed into an APL array where every item represents a record. Data masked by " remain unchanged. The functions can deal with files from Unix, Mac and Windows.
r←PartitionRecordsWithDyalog string;masked;cr;lf;bool ⍝ Takes a string and partitions records. ⍝ Can deal with Mac/Unix/Windows files. ⍝ For that, CR+LF as well as single LFs are converted into CR. ⍝ CR is then used to partition "string". ⎕IO←1 ⋄ ⎕ML←3 (cr lf)←⎕UCS 10 13 ⍝ <CarriageReturn> and <LineFeed> :If 0<+/bool←(cr,lf)⍷string ⍝ are there any cr+lf in "string"? string←(~bool)/string ⍝ Let only the cr survive :EndIf :If 0<+/bool←cr=string ⍝ Are there still any cr's? (bool/string)←lf ⍝ Convert them to lf :EndIf ⍝ In the remaining string, there might be lf's inside text, Those ⍝ need to be masked before we decide where records really start. masked←~{⍵∨≠\⍵}'"'=string ⍝ what is not escaped (between "") :If 1∊bool←lf=masked/string ⍝ are there any unmasked lf in "string"? r←(~masked\bool)⊂string :Else ⍝ so it's a single record r←⊂string :EndIf
Second step: extract the real data
r←{sep}Csv2MatrixWithDyalog csv;bool;⎕IO ⍝ Convert vector-of-text-vectors "csv" that is assumed to ⍝ come from a *.csv file and which got already partitioned ⍝ into an APL matrix. Takes care of escaped stuff etc. ⍝ "sep" defaults to a comma. ⎕IO←1 ⋄ ⎕ML←3 sep←{2=⎕NC ⍵:⍎⍵ ⋄ ','}'sep' r←(⌽∨\0≠⌽↑∘⍴¨csv)/csv ⍝ remove empty stuff from the end if any r←',',¨r ⍝ Add starting seperator bool←{~{⍵∨≠\⍵}'"'=⍵}¨r ⍝ prepare booleans useful to mask escaped stuff r←r{⎕ML←1 ⋄ ⍺⊂⍨⍵=sep}¨bool{⍺\⍺/⍵}¨r ⍝ partition fields by unmasked commas r←⊃{1↓¨⍵}¨r ⍝ Drop command and transform to a matrix r←{'"'≠1⍴⍵:⍵ ⋄ ¯1↓1↓⍵}¨r ⍝ remove leading and trailing " r←Csv2Numeric r ⍝ Convert numeric cells r←(~'""'∘⍷¨r)/¨r ⍝ double-" into a single one
r←{ignore}Csv2Numeric r;buffer ⍝ Transform cells that contain digits into numeric values, BUT: ⍝ * Commas are ignored. ⍝ * "$£€¥" are ignored because the left argument "ignore" defaults to those. ⍝ * Blanks are removed ⍝ Example: ⍝ (¯10 3 4 1234.5 12 1000 '1A')←Csv2Numeric '-10' '3' '4' '123,4.5' '£12' '1E3' '1A' ignore←{0<⎕NC ⍵:⍎⍵ ⋄ '$£€¥'}'ignore' buffer←{0=+/bool←'-'=w←⍵:⍵ ⋄ (bool/w)←'¯' ⋄ w}¨r ⍝ "buffer" is a copy of r with "¯" for "-" r←buffer{(0∊⍴⍵):'' ⋄ ,↑1⊃v←⎕VFI ⍺~' ,',ignore:↑2⊃v ⋄ ⍵}¨r ⍝ make fields with appropriate content numeric
The Final Step
Put it all together:
r←{sep} DealWithCsv filename;data ⍝ Read "filename" which is assumed to be a *.csv file ⍝ and convert it into a matrix sep←{2=⎕NC ⍵:⍎⍵ ⋄ ','}'sep' data←FileRead filename data←PartitionRecordsWithDyalog data r←sep Csv2MatrixWithDyalog data
The resulting variable in APL would look like this:
Note that the 1 in the second row/second column got converted into the number because the contents of the cell remained of digits only. However, in the original Excel spreadsheet that cell is text; this is indicated by the small green triangle. This information is not contained in the CSV file.
Writing a CSV file using Dyalog APL
Given an APL array like:
⎕←2 3⍴'APL' 'is' 'fine, very fine' 1 2.2 ¯3 APL is fine, very fine 1 2.2 ¯3
The following function takes such an array as right argument and converts it into a string that can be written to a file with the extension ".csv". The left argument defaults to "windows" and can be "unix" or "mac" as well. Note that the left argument is case sensitive. The left argument is used to determine the appropriate record separator.
r←{os}Array2CsvWithDyalog array;cr;lf;sep;bool;IsChar;dq ⎕IO←1 ⋄ ⎕ML←3 :If 0=⎕NC'os' os←'windows' :EndIf 'Invalid left argument; must be one of: windows, unix, mac'⎕SIGNAL 11/⍨~(⊂os)∊'windows' 'unix' 'mac' 'Right argument must have a depth of 2'⎕SIGNAL 11/⍨2≠≡array 'Right argument must be either a matrix or a vector'⎕SIGNAL 11/⍨~(⍴⍴array)∊1 2 (cr lf)←⎕TC[2 3] ⍝ <CarriageReturn> and <LineFeed> sep←('windows' 'unix' 'mac'⍳⊂os)⊃(cr,lf)lf cr ⍝ select proper record separator IsChar←{0 2∊⍨10|⎕DR ⍵} ⍝ Version 12 compatible bool←,~IsChar¨array ⍝ locate number (bool/,array)←⍕¨bool/,array ⍝ make numbers text dq←,'"'∊¨array ⍝ Where are double quotes in the text? (dq/,array)←{b←'"'=w←⍵ ⋄ (b/w)←⊂'""' ⋄ ⊃,/w}¨dq/,array ⍝ Double the double quotes bool←dq∨,(lf∊¨array)∨','∊¨array ⍝ where are special chars used? (bool/,array)←{'"',⍵,'"'}¨bool/,array ⍝ escape field with special chars bool←'"'∊¨array ⍝ where are special chars used? array←{⊃{⍺,',',⍵}/⍵}¨↓array ⍝ separate fields by comma r←⊃,/array,¨⊂sep ⍝ make it simpel ((r='¯')/r)←'-'
⍝ Example: #.Array2CsvWithDyalog 2 3⍴'APL' 'really "really" is' 'fine, very fine' 1 2.2 ¯3 APL,"really ""really"" is","fine, very fine" 1,2.2,-3
Author: KaiJaeger
Update -- KaiJaeger 2012-08-05 11:06:46 incorporating a couple of findings/suggestions from EllisMorgan. |
Update -- KaiJaeger 2015-03-24 11:26:39 bug fix: empty cells were not handled correctly. |