converting pipe seperated raw data to xlsx using xlsxwriter module of python - python-2.7

I'm new to python and trying to write a small code to convert raw pipe seperated data to xlsx. Details as below :
raw data
a|b|c|d|
.
.
.
1000s of row
expected output
a b c d {each representing one cell in xlsx}
My code:
workbook=xlsxwriter.Workbook('ABC.xlsx')
worksheet=workbook.add_worksheet()
input_file=(raw_data.txt,'r')
row=0
col=0
for line in input_file:
line=line.split('|')
workseet.write(row,col,line)
row +=1
worsheet.close()
The output that i'm getting is :
a b c d (all in single cell)
Any pointers on what i'm missing here will be helpful.

Related

Read multiple excel sheets on specific column and right them in one csv file using python

I have multiple sheets in one excel file like Sheet1, Sheet2, Sheet3,etc. Now I have to list all the particular column in one csv file. Both the sheets has one unique column "Attribute" and only those records should be listed in the csv file line by line. (First sheet's 'Attribute' values should be in 1st line and 2nd sheet's 'Attribute' values should be in 2nd line and etc.,)
If instances,
Sheet1:
Attribute,Order
P,1
Emp_ID,2
DOJ,3
Name,4
Sheet2:
Attribute,Order
C,1
Emp_ID,2
Exp,3
LWD,4
Expected result: (In some .csv file)
P,Emp_ID,DOJ,name
C,Emp_ID,Exp,LWD
Note: Line starting from P should be in first line and C should be in 2nd line and etc.,
Below is my code:
import pandas as pd
excel = 'E:\Python Utility\Inbound.xlsx'
K = 'E:\Python Utility\Headers_Files\All_Header.csv'
df = pd.read_excel(excel,sheet_name = None)
data = pd.DataFrame(df,columns=['Attribute']).T
print data
M = data.to_csv(K, encoding='utf-8',index=False,header=False)
print 'done'
Output show's as below:
Empty DataFrame Columns: [] Index: [Attribute] done
If I use sheet_name = 'sheet1' then DataFrame works good and data loaded as expected in csv file.
Thanks in advance

reading in certain rows from a csv file using python

Say I have a csv file that looks like the following with the first column containing frequencies and the second column containing the power level (dBm).
Frequency | dBm
1 -11.43
2.3 -51.32
2.5 -12.11
2.8 -11.21
3.1 -73.22
3.2 -21.13
I only want to read in the data sets of this file that have a (dBm) value between -13 and -10. Therefore, in this example I only want the data sets (1, -11.43)(2.5, -12.11)(2.8, -11.21) to be read into my program variables x1 and y1. Could someone give me some help in how I could do this?
You can just use the csv library and check if each meets your criteria.
Something like this should work on your file:
with open('file.csv') as csvfile:
reader = csv.reader(csvfile,delimiter=' ')
reader.next()
reader.next()
for row in reader:
a = [float(i) for i in row if i!='']
if a[1]>=-13 and a[1]<=-1:
print (a[0],a[1])
Edit: If you're working with table data I would suggest trying out Pandas, it's really helpful in these situations.

Using Python CSV and glob to find matching strings and print row

I have hundreds of CSV files and I'm trying to write a Python script that will parse through all of them and print out rows that have matching string(s). I'll be happy if we can get this to work using one string (and not a list of strings). Using Python 2.7.5. I've figured out so far:
The csv module in Python will print the row with the matching string in a particular column (the eighth column from the left):
import csv
reader = csv.reader(open('2015-08-25.csv'))
for row in reader:
col8 = str(row[8])
if col8 == '36862210':
print row
So the above works for one .csv file. Now I need to parse hundreds of .csv files with glob. The glob module will print out all the file names with this code:
import glob
for name in glob.glob('20??-??-??.csv'):
print name
I tried putting the two together into one script but the error message reads:
File "test7.py", line 6, in
reader = csv.reader(open(csvfiles))
TypeError: coercing to Unicode: need string or buffer, list found
import csv
import glob
csvfiles = glob.glob('20??-??-??.csv')
for filename in csvfiles:
reader = csv.reader(open(csvfiles))
for row in reader:
col8 = str(row[8])
if col8 == '36862210':
print row
You are trying to open a List - csvfiles is the list you are iterating on.
Use this instead, because open() expects a filename:
reader = csv.reader(open(filename))

How do I iterate a loop over several data frames in a list in python

I am very new to programming and am working with Python. For a work project I am trying to read several .csv files, convert them to data frames, concatenate some of the fields into one for a column header, and then append all of the dataframes into one big DataFrame. I have searched extensively in StackOverflow as well as in other resources but I have not been able to find an answer. Here is the code I have thus far along with some abbreviated output:
import pandas as pd
import glob
# Read a directory of files to a list
csvlist = []
for f in glob.glob("AssayCerts/*"):
csvlist.append(f)
csvlist
['AssayCerts/CH09051590.csv', 'AssayCerts/CH09051591.csv', 'AssayCerts/CH14158806.csv', 'AssayCerts/CH14162453.csv', 'AssayCerts/CH14186004.csv']
# Read .csv files and convert to DataFrames
dflist = []
for csv in csvlist:
df = pd.read_csv(filename, header = None, skiprows = 7)
dflist.append(df)
dflist
[ 0 1 2 3 4 5 \
0 NaN Au-AA23 ME-ICP41 ME-ICP41 ME-ICP41 ME-ICP41
1 SAMPLE Au Ag Al As B
2 DESCRIPTION ppm ppm % ppm ppm
#concatenates the cells in the first three rows of the last dataframe; need to apply this to all of the dataframes.
for df in dflist:
column_names = df.apply(lambda x: str(x[1]) + '-'+str(x[2])+' - '+str(x[0]),axis=0)
column_names
0 SAMPLE-DESCRIPTION - nan
1 Au-ppm - Au-AA23
2 Ag-ppm - ME-ICP41
3 Al-% - ME-ICP41
I am unable to apply the last operation across all of the DataFrames. It seems I can only get it to apply to the last DataFrame in my list. Once I get past this point I will have to append all of the DataFrames to form one large DataFrame.
As Andy Hayden mentions in his comment, the reason your loop only appears to work on the last DataFrame is that you just keep assigning the result of df.apply( ... ) to column_names, which gets written over each time. So at the end of the loop, column_names always contains the results from the last DataFrame in the list.
But you also have some other problems in your code. In the loop that begins for csv in csvlist:, you never actually reference csv - you just reference filename, which doesn't appear to be defined. And dflist just appears to have one DataFrame in it anyway.
As written in your problem, the code doesn't appear to work. I'd advise posting the real code that you're using, and only what's relevant to your problem (i.e. if building csvlist is working for you, then you don't need to show it to us).

Extracting columnar data correctly as it is in the file

Suppose i have tabular column as below.Now i want to extract the column wise data.I tried extracting data by creating a list.But it is extracting the first row correctly but from second row onwards there is space i.e under CEN/4.Now my code considers zeroth column has 5.0001e-1 form second row,it starts reading from there. How to extract the data correctly coulmn wise.output is scrambled.
0 1 25 CEN/4 -5.000000E-01 -3.607026E+04 -5.747796E+03 -8.912796E+02 -88.3178
5.000000E-01 3.607026E+04 5.747796E+03 8.912796E+02 1.6822
27 -5.000000E-01 -3.641444E+04 -5.783247E+03 -8.912796E+02 -88.3347
5.000000E-01 3.641444E+04 5.783247E+03 8.912796E+02 1.6653
28 -5.000000E-01 -3.641444E+04 -5.712346E+03 -8.912796E+02 -88.3386
5.000000E-01 3.641444E+04 5.712346E+03 8.912796E+02
my code is :
f1=open('newdata1.txt','w')
L = []
for index, line in enumerate(open('Trial_1.txt','r')):
#print index
if index < 0: #skip first 5 lines
continue
else:
line =line.split()
L.append('%s\t%s\t %s\n' %(line[0], line[1],line[2]))
f1.writelines(L)
f1.close()
my output looks like this:
0 1 CEN/4 -5.000000E-01 -5.120107E+04
5.000000E-01 5.120107E+04 1.028093E+04 5.979930E+03 8.1461
i want columnar data as it is in the file.How to do that.I am a bgeinner
its hard to tell from the way the input data is presented in your question, but Im guessing your file is using tabs to separate columns, in any case, consider using python csv module with the relevant delimiter like:
import csv
with open('input.csv') as f_in, open('newdata1', 'w') as f_out:
reader = csv.reader(f_in, delimiter='\t')
writer = csv.writer(f_out, delimiter='\t')
for row in reader:
writer.writerow(row)
see python csv module documentation for further details