File 1
---------+
|ID |
+---------+
| 15 |
| 45 |
| 18 |
| 76 |
| 29 |
| 10 |
| 40 |
+---------+
File 2:
| ID Name |
+---------+
| 12 abc |
| 18 nop |
| 15 ujh |
| 30 jkl |
| 15 lmn |
| 18 tre |
| 19 hgt |
+---------+
Desired output:
+---------+
| ID Name |
+---------+
| 18 nop |
| 15 ujh |
| 15 lmn |
| 18 tre |
+---------
The Join cammand below is not giving the desired result (It should return all rows in File 2 where the value in the first column exists in the File1 table.
join -1 1 -2 1 File1.txt File2.txt
Please help.
Well, since you ask specifically for an awk solution, here's one approach:
#!/bin/sh
awk 'BEGIN {
while ((getline line < "File1.txt") > 0) {
split(line, a)
for (fld in a) {
if (a[fld] ~ /^[0-9]*$/ ) {
targets[a[fld]]=a[fld]
}
}
}
} {
if (NF == 4 && $2 ~ /^[0-9]*$/ ) {
if ($2 in targets) {
print $0
}
} else {
print $0
}
}' File2.txt
Although, I wonder like #Mark Setchell why you wouldn't approach getting this output from the database, if you have access to it.
Related
So let's say I have a table in my Sqlite database with some information about some files, with the following structure:
| id | file format | creation date |
----------------------------------------------------------
| 1 | Word | 2010:02:12 13:31:33+01:00 |
| 2 | PSD | 2021:02:23 15:44:51+01:00 |
| 3 | Word | 2019:02:13 14:18:11+01:00 |
| 4 | Word | 2010:02:12 13:31:20+01:00 |
| 5 | Word | 2003:05:25 18:55:10+02:00 |
| 6 | PSD | 2014:07:20 20:55:58+02:00 |
| 7 | Word | 2014:07:20 21:09:24+02:00 |
| 8 | TIFF | 2011:03:30 11:56:56+02:00 |
| 9 | PSD | 2015:07:15 14:34:36+02:00 |
| 10 | PSD | 2009:08:29 11:25:57+02:00 |
| 11 | Word | 2003:05:25 20:06:18+02:00 |
I would like results that show me a chronology of how many of each file format were created in a given year – something along the lines of this:
|Format| 2003 | 2009 | 2010 | 2011 | 2014 | 2015 | 2019 | 2021 |
----------------------------------------------------------------
| Word | 2 | 0 | 0 | 2 | 0 | 0 | 2 | 0 |
| PSD | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 1 |
| TIFF | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 |
I've gotten kinda close (I think) with this, but am stuck:
SELECT
file_format,
COUNT(CASE file_format WHEN creation_date LIKE '%2010%' THEN 1 ELSE 0 END),
COUNT(CASE file_format WHEN creation_date LIKE '%2011%' THEN 1 ELSE 0 END),
COUNT(CASE file_format WHEN creation_date LIKE '%2012%' THEN 1 ELSE 0 END)
FROM
fileinfo
GROUP BY
file_format;
When I do this I am getting unique amounts for each file format, but the same count for every year…
|Format| 2010 | 2011 | 2012 |
-----------------------------
| Word | 4 | 4 | 4 |
| PSD | 1 | 1 | 1 |
| TIFF | 6 | 6 | 6 |
Why am I getting that incorrect tally, and moreover, is there a smarter way of querying that doesn't rely on the year being statically searched for as a string for every single year? If it helps, the column headers and row headers could be switched – doesn't matter to me. Please help a n00b :(
Use SUM() aggregate function for conditional aggregation:
SELECT file_format,
SUM(creation_date LIKE '2010%') AS `2010`,
SUM(creation_date LIKE '2011%') AS `2011`,
..........................................
FROM fileinfo
GROUP BY file_format;
See the demo.
I am cleaning the data using R.
Below is my data format
Input
1) 100 | 101.25 | 102.25. | . | .. | 201.5. |
2) 200.05. | 200.56. | 205 | .. | . | 3000 |
3) 300.98 | 300.26. | 2001.56.| ... | 0.2| 5.65. |
expected output:
1) 100 | 101.25 | 102.25 |NA | NA |201.5
2) 200.05|200.26 | 205 |NA | NA |3000
3) 300.98|300.26 |2001.26 |NA |0.2 |5.65
there are extra full stops at in the table, which I am trying to get cleaned, but to retain decimal numbers in its format
I tried replace all in R, which clears all the full stops, and decimal numbers are distorted.
If the trailing full stop is really the only manifestation of the problem, then you may try just removing it with sub:
x <- c("101.25", "200.56.", "300.26")
x <- sub("\\.$", "", x)
You can use look-ahead to replace dot(.) which are not before space or | as:
x <- '1) 100 | 101.25 | 102.25. | . | .. | 201.5. |
2) 200.05. | 200.56. | 205 | .. | . | 3000 |
3) 300.98 | 300.26. | 2001.56.| ... | 0.2| 5.65. |'
y <- gsub("([.]+)(?=[[:blank:]|])","",x,perl = TRUE)
cat(y)
# 1) 100 | 101.25 | 102.25 | | | 201.5 |
# 2) 200.05 | 200.56 | 205 | | | 3000 |
# 3) 300.98 | 300.26 | 2001.56| | 0.2| 5.65 |
Regex explanation:
([.]+) - Group any number of . before look-ahead
(?=[[:blank:]|]) - Look-ahead before :blank: or |
Data:
x <- '1) 100 | 101.25 | 102.25. | . | .. | 201.5. |
2) 200.05. | 200.56. | 205 | .. | . | 3000 |
3) 300.98 | 300.26. | 2001.56.| ... | 0.2| 5.65. |'
I have 2 dataframes
Dataframe1:
| Cue | Ass_word | Condition | Freq | Cue_Ass_word |
1 | ACCENDERE | ACCENDINO | A | 1 | ACCENDERE_ACCENDINO
2 | ACCENDERE | ALLETTARE | A | 0 | ACCENDERE_ALLETTARE
3 | ACCENDERE | APRIRE | A | 1 | ACCENDERE_APRIRE
4 | ACCENDERE | ASCENDERE | A | 1 | ACCENDERE_ASCENDERE
5 | ACCENDERE | ATTIVARE | A | 0 | ACCENDERE_ATTIVARE
6 | ACCENDERE | AUTO | A | 0 | ACCENDERE_AUTO
7 | ACCENDERE | ACCENDINO | B | 2 | ACCENDERE_ACCENDINO
8 | ACCENDERE| ALLETTARE | B | 3 | ACCENDERE_ALLETTARE
9 | ACCENDERE| ACCENDINO | C | 2 | ACCENDERE_ACCENDINO
10 | ACCENDERE| ALLETTARE | C | 0 | ACCENDERE_ALLETTARE
Dataframe2:
| Group.1 | x
1 | ACCENDERE_ACCENDINO | 5
13 | ACCENDERE_FUOCO | 22
16 | ACCENDERE_LUCE | 10
24 | ACCENDERE_SIGARETTA | 6
....
I want to exclude from Dataframe1 all the rows that contain words (Cue_Ass_word) that are not reported in the column Group.1 in Dataframe2.
In other words, how can I subset Dataframe1 using the strings reported in Dataframe2$Group.1?
It's not quite clear what you mean, but is this what you need?
Dataframe1[!(Dataframe1$Cue_Ass_word %in% Dataframe2$Group1),]
I load a text file (tree.txt) to R, with the below content (copy pasted from JWEKA - J48 command).
I use the following command to load the text file:
data3 <-read.table (file.choose(), header = FALSE,sep = ",")
I would like to insert each column into a separate variables named like the following format COL1, COL2 ... COL8 (in this example since we have 8 columns). If you load it to EXCEL with delimited separation each row will be separated in one column (this is the required result).
Each COLn will contain the relevant characters of the tree in this example.
How can separate and insert the text file into these columns automatically while ignoring the header and footer content of the file?
Here is the text file content:
[[1]]
J48 pruned tree
------------------
MSTV <= 0.4
| MLTV <= 4.1: 3 -2
| MLTV > 4.1
| | ASTV <= 79
| | | b <= 1383:00:00 2 -18
| | | b > 1383
| | | | UC <= 05:00 1 -2
| | | | UC > 05:00 2 -2
| | ASTV > 79:00:00 3 -2
MSTV > 0.4
| DP <= 0
| | ALTV <= 09:00 1 (170.0/2.0)
| | ALTV > 9
| | | FM <= 7
| | | | LBE <= 142:00:00 1 (27.0/1.0)
| | | | LBE > 142
| | | | | AC <= 2
| | | | | | e <= 1058:00:00 1 -5
| | | | | | e > 1058
| | | | | | | DL <= 04:00 2 (9.0/1.0)
| | | | | | | DL > 04:00 1 -2
| | | | | AC > 02:00 1 -3
| | | FM > 07:00 2 -2
| DP > 0
| | DP <= 1
| | | UC <= 03:00 2 (4.0/1.0)
| | | UC > 3
| | | | MLTV <= 0.4: 3 -2
| | | | MLTV > 0.4: 1 -8
| | DP > 01:00 3 -8
Number of Leaves : 16
Size of the tree : 31
An example of the COL1 content will be:
MSTV
|
|
|
|
|
|
|
|
MSTV
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
COL2 content will be:
MLTV
MLTV
|
|
|
|
|
|
>
DP
|
|
|
|
|
|
|
|
|
|
|
|
DP
|
|
|
|
|
|
Try this:
cleaned.txt <- capture.output(cat(paste0(tail(head(readLines("FILE_LOCATION"), -4), -4), collapse = '\n'), sep = '\n'))
cleaned.df <- read.fwf(file = textConnection(cleaned.txt),
header = FALSE,
widths = rep.int(4, max(nchar(cleaned.txt)/4)),
strip.white= TRUE
)
cleaned.df <- cleaned.df[,colSums(is.na(cleaned.df))<nrow(cleaned.df)]
For the cleaning process, I end up using a combination of head and tail to remove the 4 spaces on the top and the bottom. There's probably a more efficient way to do this outside of R, but this isn't so bad. Generally, I'm just making the file readable to R.
Your file looks like a fixed-width file so I use read.fwf, and use textConnection() to point the function to the cleaned output.
Finally, I'm not sure how your data is actually structured, but when I copied it from stackoverflow, it pasted with a bunch of whitespace at the end of each line. I'm using some tricks to guess at how long the file is, and removing extraneous columns over here
widths = rep.int(4, max(nchar(cleaned.txt)/4))
cleaned.df <- cleaned.df[,colSums(is.na(cleaned.df))<nrow(cleaned.df)]
Next, I'm creating the data in the way you would like it structured.
for (i in colnames(cleaned.df)) {
assign(i, subset(cleaned.df, select=i))
assign(i, capture.output(cat(paste0(unlist(get(i)[get(i)!=""])),sep = ' ', fill = FALSE)))
}
rm(i)
rm(cleaned.df)
rm(cleaned.txt)
What this does is it creates a loop for each column header in your data frame.
From there it uses assign() to put all the data in each column into its' own data frame. In your case, they are named V1 through V15.
Next, it uses a combination of cat() and paste() with unlist() an capture.output() to concatenate your list into a single character vectors, for each of the data frames, so they are now character vectors, instead of data frames.
Keep in mind that because you wanted a space at each new character, I'm using a space as a separator. But because this is a fixed-width file, some columns are completely blank, which I'm removing using
get(i)[get(i)!=""]
(Your question said you wanted COL2 to be: MLTV MLTV | | | | | | > DP | | | | | | | | | | | | DP | | | | | |).
If we just use get(i), there will be a leading whitespace in the output.
I have the following decision tree (created by JWEKA package - by the command J48(NSP~., data=training) ):
[[1]]
J48 pruned tree
------------------
MSTV <= 0.4
| MLTV <= 4.1: 3 -2
| MLTV > 4.1
| | ASTV <= 79
| | | b <= 1383:00:00 2 -18
| | | b > 1383
| | | | UC <= 05:00 1 -2
| | | | UC > 05:00 2 -2
| | ASTV > 79:00:00 3 -2
MSTV > 0.4
| DP <= 0
| | ALTV <= 09:00 1 (170.0/2.0)
| | ALTV > 9
| | | FM <= 7
| | | | LBE <= 142:00:00 1 (27.0/1.0)
| | | | LBE > 142
| | | | | AC <= 2
| | | | | | e <= 1058:00:00 1 -5
| | | | | | e > 1058
| | | | | | | DL <= 04:00 2 (9.0/1.0)
| | | | | | | DL > 04:00 1 -2
| | | | | AC > 02:00 1 -3
| | | FM > 07:00 2 -2
| DP > 0
| | DP <= 1
| | | UC <= 03:00 2 (4.0/1.0)
| | | UC > 3
| | | | MLTV <= 0.4: 3 -2
| | | | MLTV > 0.4: 1 -8
| | DP > 01:00 3 -8
Number of Leaves : 16
Size of the tree : 31
I would like to extract the nodes' values in 2 formats:
one format only the name of the property such as: MSTV, MLTV, DP... etc.,
So each level of the tree will be followed by his parent, in the above case I would like to get the '(' as separator between each level such as:
(MSTV (MLTV...) (DP...) )
In the second format I would like to get the nodes with their values such as:
(MSTV 0.4 (MLTV 4.1 ....) (DP 0..... ) )
How can I extract the relevant information. I think to separate between the node values we should separate the characters by using gsub("[A-Z]:", "", string)
But we need to ignore the last lines.
Thanks a lot for your help.