I am using Pandas to organize CSV files to later plot with matplotlib. First I create a Pandas dataframe to find the line containing 'Pt'. This is what I search for to use as my header line. header
Then I save the index of this line and apply it to the skiprow argument when creating the new dataframe which I will use.
Oddly, depending on the file format, even though the correct index is found, the wrong line shows up as the header. For example, note how in Pandas line 54 has 'Pt" right after the tab:
correct index on first file
The dataframe comes out correctly here.
correct dataframe on first file
For another file, line 44 is correctly recognized with having 'Pt'.
correct index on second file
But the dataframe includes line 43 as the header!
incorrect dataframe on second file
I have tried setting header=0, header=none. Am I missing something?
Here is the code
entire_df = pd.read_csv(file_path, header=None)
print(entire_df.head(60))
header_idx = -1
for index, row in entire_df.iterrows(): # find line with desired header
if any(row.str.contains('Pt')):
print("Yes! I have pt!")
print("Header index is: " + str(index))
print("row contains:")
print(entire_df.loc[[index]])
header_idx = index # correct index obtained!
break
df = pd.read_csv(file_path, delimiter='\t', skiprows=header_idx, header=0) # use line index to exclude extra information above
print(df.head())
Here are sections of the two files that give different results. They are saved as .dta files. I cannot share the entire files.
file1 (properly made dataframe)
FRAMEWORKVERSION QUANT 7.07 Framework Version
INSTRUMENTVERSION LABEL 4.32 Instrument Version
CURVE TABLE 16875
Pt T Vf Im Vu Pwr Sig Ach Temp IERange Over
# s V A V W V V deg C # bits
0 0.1 3.49916E+000 -1.40364E-002 0.00000E+000 -4.91157E-002 -4.22328E-001 0.00000E+000 1.41995E+003 11 ...........
1 0.2 3.49439E+000 -1.40305E-002 0.00000E+000 -4.90282E-002 -4.22322E-001 0.00000E+000 1.41995E+003 11 ...........
2 0.3 3.49147E+000 -1.40258E-002 0.00000E+000 -4.89705E-002 -4.22322E-001
file2 (dataframe with wrong header)
FRAMEWORKVERSION QUANT 7.07 Framework Version
INSTRUMENTVERSION LABEL 4.32 Instrument Version
CURVE TABLE 18
Pt T Vf Vm Ach Over Temp
# s V vs. Ref. V V bits deg C
0 2.00833 3.69429E+000 3.69429E+000 0.00000E+000 ........... 1419.95
1 4.01667 3.69428E+000 3.69352E+000 0.00000E+000 ........... 1419.95
2 6.025 3.69419E+000 3.69284E+000 0.00000E+000 ........... 1419.95
3 8.03333 3.69394E+000 3.69211E+000 0.00000E+000 ........... 1419.95
Help would be much appreciated.
You should pay attention to your indentation levels. Your code block in which you want to set the header_idx depending on your if any(row.str.contains('Pt')) condition has the same intendation level as the if statement, which means it is executed at each iteration of the for loop, and not just when the condition is met.
for index, row in entire_df.iterrows():
if any(row.str.contains('Pt')):
[...]
header_idx = index
Adapt the indentation like that to put the assignment under the control of the if statement:
for index, row in entire_df.iterrows():
if any(row.str.contains('Pt')):
[...]
header_idx = index
Related
I need help solving this problem:
I have a directory full of .txt files that look like this:
file1.no
file2.no
file3.no
And every file has the following structure (I only care for the first two "columns" in the .txt):
#POS SEQ SCORE QQ-INTERVAL STD MSA DATA
#The alpha parameter 0.75858
#The likelihood of the data given alpha and the tree is:
#LL=-4797.62
1 M 0.3821 [0.01331,0.5465] 0.4421 7/7
2 E 0.4508 [0.05393,0.6788] 0.5331 7/7
3 L 0.5334 [0.05393,0.6788] 0.6279 7/7
4 G 0.5339 [0.05393,0.6788] 0.624 7/7
And I want to parse all of them into one DataFrame, while also converting the columns into lists for each row (i.e., the first column should be converted into a string like this: ["MELG"]).
But now I am running into two issues:
How to read the different files and append all of them to a single DataFrame, and also making a single column out of al the rows inside said files
How to parse this files, giving that the spaces between the columns vary for almost all of them.
My output should look like this:
|File |SEQ |SCORE|
| --- | ---| --- |
|File1|MELG|0.3821,0.4508,0.5334,0.5339|
|File2|AAHG|0.5412,1,2345,0.0241,0.5901|
|File3|LLKM|0.9812,0,2145,0.4142,0.4921|
So, the first column for the first file (file1.no), the one with single letters, is now in a list, in a row with all the information from that file, and the DataFrame has one row for each file.
Any help is welcome, thanks in advance.
Here is an example code that should work for you:
using DataFrames
function parsefile(filename)
l = readlines(filename)
filter!(x -> !startswith(x, "#"), l)
sl = split.(l)
return (File=filename,
SEQ=join(getindex.(sl, 2)),
SCORE=parse.(Float64, getindex.(sl, 3)))
end
df = DataFrame()
foreach(fn -> push!(df, parsefile(fn)), ["file$i.no" for i in 1:3])
your result will be in df data frame.
I am trying to get my head around the Pandas module and started learning about the Series data structure.
I have created the following Series in Spyder :-
songs = pd.Series(data = [145,142,38,13], name = "Count")
I can obtain information about the Series index using the code:-
songs.index
The output of the above code is as follows:-
My question is where it states Start = 0 and Stop = 4, what are these referring to?
I have interpreted start = 0 as the first element in the Series is in row 0.
But i am not sure what Stop value refers to as there are no elements in row 4 of the Series?
Can some one explain?
Thank you.
This concept as already explained adequately in the comments (indexing is at minus one the count of items) is prevalent in many places.
For instance, take the list data structure-
z = songs.to_list()
[145, 142, 38, 13]
len(z)
4 # length is four
# however indexing stops at i-1 position 'i' being the length/count of items in the list.
z[4] # this will raise an IndexError
# you will have to start at index 0 going till only index 3 (i.e. 4 items)
z[0], z[1], z[2], z[-1] # notice how -1 can be used to directly access the last element
I have a data in the following form:
product/productId B000EVS4TY
1 product/title Arrowhead Mills Cookie Mix, Chocolate Chip, 1...
2 product/price unknown
3 review/userId A2SRVDDDOQ8QJL
4 review/profileName MJ23447
5 review/helpfulness 2/4
6 review/score 4.0
7 review/time 1206576000
8 review/summary Delicious cookie mix
9 review/text I thought it was funny that I bought this pro...
10 product/productId B0000DF3IX
11 product/title Paprika Hungarian Sweet
12 product/price unknown
13 review/userId A244MHL2UN2EYL
14 review/profileName P. J. Whiting "book cook"
15 review/helpfulness 0/0
16 review/score 5.0
17 review/time 1127088000
I want to convert it to a dataframe such that the entries in the 1st column
product/productId
product/title
product/price
review/userId
review/profileName
review/helpfulness
review/score
review/time
review/summary
review/text
are the column headers with the values arranged corresponding to each header in the table.
I still had a tiny doubt about your file, but since both my suggestions are quite similar, I will try to address both the scenarios you might have.
In case your file doesn't actually have the line numbers inside of it, this should do it:
filepath = "./untitled.txt" # you need to change this to your file path
column_separator="\s{3,}" # we'll use a regex, I explain some caveats of this below...
# engine='python' surpresses a warning by pandas
# header=None is that so all lines are considered 'data'
df = pd.read_csv(filepath, sep=column_separator, engine="python", header=None)
df = df.set_index(0) # this takes column '0' and uses it as the dataframe index
df = df.T # this makes the data look like you were asking (goes from multiple rows+1column to multiple columns+1 row)
df = df.reset_index(drop=True) # this is just so the first row starts at index '0' instead of '1'
# you could just do the last 3 lines with:
# df = df.set_index(0).T.reset_index(drop=True)
If you do have line numbers, then we just need to do some little adjustments
filepath = "./untitled1.txt"
column_separator="\s{3,}"
df = pd.read_csv(filepath, sep=column_separator, engine="python", header=None, index_col=0)
df.set_index(1).T.reset_index(drop=True) #I did all the 3 steps in 1 line, for brevity
In this last case, I would advise you change it in order to have line numbers in all of them (in the example you provided, the numbering starts at the second line, this might be an option about how you handle headers when exporting the data in whatever tool you might be using
Regarding the regex, the caveat is that "\s{3,}" looks for any block of 3 consecutive whitespaces or more to determine the column separator. The problem here is that we'll depend a bit on the data to find the columns. For instance, if in any of the values just so happens to appear 3 consecutive spaces, pandas will raise an exception, since the line will have one more column than the others. One solution to this could be increasing it to any other 'appropriate' number, but then we still depend on the data (for instance, with more than 3, in your example, "review/text" would have enough spaces for the two columns to be identified)
edit after realising what you meant by "stacked"
Whatever "line-number scenario" you have, you'll need to make sure you always have the same number of columns for all registers and reshape the continuous dataframe with something similar to this:
number_of_columns = 10 # you'll need to make sure all "registers" do have the same number of columns otherwise this will break
new_shape = (-1,number_of_columns) # this tuple will mean "whatever number of lines", by 10 columns
final_df = pd.DataFrame(data = df.values.reshape(new_shape)
,columns=df.columns.tolist()[:-10])
Again, take notice of making sure that all lines have the same number of columns (for instance, a file with just the data you provided, assuming 10 columns, wouldn't work). Also, this solution assumes all columns will have the same name.
I have a similiar problem like this question:
selecting every Nth column in using SQLDF or read.csv.sql
I want to read some columns of large files (table of 150rows, >500,000 columns, space separated, filled with numeric data and only a 32 bit system available). This file has no header, therefore the code in the thread above didn't work and I decided to write a new post.
Do you have an idea to solve this problem?
I thought about something like that, but any results with fread or read.table are also ok:
MyConnection <- file("path/file.txt")
df<-sqldf("select column 1 100 1000 235612 from MyConnection",file.format = list(header=F,sep=" "))
You can use substr to specify the start and end position of the columns you want to read in if they are fixed width:
x <- tempfile()
cat("12345", "67890", "09876", "54321", sep = "\n", file = x)
myfile <- file(x)
sqldf("select substr(V1, 1, 1) var1, substr(V1, 3, 5) var2 from myfile")
# var1 var2
# 1 1 345
# 2 6 890
# 3 9 76
# 4 5 321
See this blog post for some more examples. The "select" statement can easily be constructed with paste if you know the details about the column starting positions and widths.
OSX v10.6.8 and Gnuplot v4.4
I have a data file with 8 columns. I would like to take the first value from the 6th column and make it the title. Here's what I have so far:
#m1 m2 q taua taue K avgPeriodRatio time
#1 2 3 4 5 6 7 8
K = #read in data here
graph(n) = sprintf("K=%.2e",n)
set term aqua enhanced font "Times-Roman,18"
plot file using 1:3 title graph(K)
And here is what the first few rows of my data file looks like:
1.00e-07 1.00e-07 1.00e+00 1.00e+05 1.00e+04 1.00e+01 1.310 12070.00
1.11e-06 1.00e-07 9.02e-02 1.00e+05 1.00e+04 1.00e+01 1.310 12070.00
2.12e-06 1.00e-07 4.72e-02 1.00e+05 1.00e+04 1.00e+01 1.310 12070.00
3.13e-06 1.00e-07 3.20e-02 1.00e+05 1.00e+04 1.00e+01 1.310 12090.00
I don't know how to correctly read in the data or if this is even the right way to go about this.
EDIT #1
Ok, thanks to mgilson I now have
#m1 m2 q taua taue K avgPeriodRatio time
#1 2 3 4 5 6 7 8
set term aqua enhanced font "Times-Roman,18"
K = "`head -1 datafile | awk '{print $6}'`"
print K+0
graph(n) = sprintf("K=%.2e",n)
plot file using 1:3 title graph(K)
but I get the error: Non-numeric string found where a numeric expression was expected
EDIT #2
file = "testPlot.txt"
K = "`head -1 file | awk '{print $6}'`"
K=K+0 #Cast K to a floating point number #this is line 9
graph(n) = sprintf("K=%.2e",n)
plot file using 1:3 title graph(K)
This gives the error--> head: file: No such file or directory
"testPlot.gnu", line 9: Non-numeric string found where a numeric expression was expected
You have a few options...
FIRST OPTION:
use columnheader
plot file using 1:3 title columnheader(6)
I haven't tested it, but this may prevent the first row from actually being plotted.
SECOND OPTION:
use an external utility to get the title:
TITLE="`head -1 datafile | awk '{print $6}'`"
plot 'datafile' using 1:3 title TITLE
If the variable is numeric, and you want to reformat it, in gnuplot, you can cast strings to a numeric type (integer/float) by adding 0 to them (e.g).
print "36.5"+0
Then you can format it with sprintf or gprintf as you're already doing.
It's weird that there is no float function. (int will work if you want to cast to an integer).
EDIT
The script below worked for me (when I pasted your example data into a file called "datafile"):
K = "`head -1 datafile | awk '{print $6}'`"
K=K+0 #Cast K to a floating point number
graph(n) = sprintf("K=%.2e",n)
plot "datafile" using 1:3 title graph(K)
EDIT 2 (addresses comments below)
To expand a variable in backtics, you'll need macros:
set macro
file="mydatafile.txt"
#THE ORDER OF QUOTES (' and ") IS CRUCIAL HERE.
cmd='"`head -1 ' . file . ' | awk ''{print $6}''`"'
# . is string concatenation. (this string has 3 pieces)
# to get a single quote inside a single quoted string
# you need to double. e.g. 'a''b' yields the string a'b
data=#cmd
To address your question 2, it is a good idea to familiarize yourself with shell utilities -- sed and awk can both do it. I'll show a combination of head/tail:
cmd='"`head -2 ' . file . ' | tail -1 | awk ''{print $6}''`"'
should work.
EDIT 3
I recently learned that in gnuplot, system is a function as well as a command. To do the above without all the backtic gymnastics,
data=system("head -1 " . file . " | awk '{print $6}'")
Wow, much better.
This is a very old question, but here's a nice way to get access to a single value anywhere in your data file and save it as a gnuplot-accessible variable:
set term unknown #This terminal will not attempt to plot anything
plot 'myfile.dat' index 0 every 1:1:0:0:0:0 u (var=$1):1
The index number allows you to address a particular dataset (separated by two carriage returns), while every allows you to specify a particular line.
The colon-separated numbers after every should be of the form 1:1:<line_number>:<block_number>:<line_number>:<block_number>, where the line number is the line with the the block (starting from 0), and the block number is the number of the block (separated by a single carriage return, again starting from 0). The first and second numbers say plot every 1 lines and every one data block, and the third and fourth say start from line <line_number> and block <block_number>. The fifth and sixth say where to stop. This allows you to select a single line anywhere in your data file.
The last part of the plot command assigns the value in a particular column (in this case, column 1) to your variable (var). There needs to be two values to a plot command, so I chose column 1 to plot against my variable assignment statement.
Here is a less 'awk'-ward solution which assigns the value from the first row and 6th column of the file 'Data.txt' to the variable x16.
set table
# Syntax: u 0:($0==RowIndex?(VariableName=$ColumnIndex):$ColumnIndex)
# RowIndex starts with 0, ColumnIndex starts with 1
# 'u' is an abbreviation for the 'using' modifier
plot 'Data.txt' u 0:($0==0?(x16=$6):$6)
unset table
A more general example for storing several values is given below:
# Load data from file to variable
# Gnuplot can only access the data via the "plot" command
set table
# Syntax: u 0:($0==RowIndex?(VariableName=$ColumnIndex):$ColumnIndex)
# RowIndex starts with 0, ColumnIndex starts with 1
# 'u' is an abbreviation for the 'using' modifier
# Example: Assign all values according to: xij = Data33[i,j]; i,j = 1,2,3
plot 'Data33.txt' u 0:($0==0?(x11=$1):$1),\
'' u 0:($0==0?(x12=$2):$2),\
'' u 0:($0==0?(x13=$3):$3),\
'' u 0:($0==1?(x21=$1):$1),\
'' u 0:($0==1?(x22=$2):$2),\
'' u 0:($0==1?(x23=$3):$3),\
'' u 0:($0==2?(x31=$1):$1),\
'' u 0:($0==2?(x32=$2):$2),\
'' u 0:($0==2?(x33=$3):$3)
unset table
print x11, x12, x13 # Data from first row
print x21, x22, x23 # Data from second row
print x31, x32, x33 # Data from third row