Develop Reference

Txt file to excel conversion in python

I'm trying to convert text file to excel sheet in python. The txt file contains data in the below specified formart
Column names: reg no, zip code, loc id, emp id, lastname, first name. Each record has one or more error numbers. Each record have their column names listed above the values. I would like to create an excel sheet containing reg no, firstname, lastname and errors listed in separate rows for each record.
How can I put the records in excel sheet ? Should I be using regular expressions ? And how can I insert error numbers in different rows for that corresponding record?
Expected output:
Here is the link to the input file:
https://github.com/trEaSRE124/Text_Excel_python/blob/master/new.txt
Any code snippets or suggestions are kindly appreciated.

Here is a draft code. Let me know if any changes needed:
# import pandas as pd
from collections import OrderedDict
from datetime import date
import csv
with open('in.txt') as f:
with open('out.csv', 'wb') as csvfile:
spamwriter = csv.writer(csvfile, delimiter=',', quoting=csv.QUOTE_MINIMAL)
#Remove inital clutter
while("INPUT DATA" not in f.readline()):
continue
header = ["REG NO", "ZIP CODE", "LOC ID", "EMP ID", "LASTNAME", "FIRSTNAME", "ERROR"]; data = list(); errors = list()
spamwriter.writerow(header)
print header
while(True):
line = f.readline()
errors = list()
if("END" in line):
exit()
try:
int(line.split()[0])
data = line.strip().split()
f.readline() # get rid of \n
line = f.readline()
while("ERROR" in line):
errors.append(line.strip())
line = f.readline()
spamwriter.writerow(data + errors)
spamwriter.flush()
except:
continue
# while(True):
# line = f.readline()
Use python-2 to run. The errors are appended as subsequent columns. It's slightly complicated the way you want it. I can fix it if still needed
Output looks like:

You can do this using the openpyxl library which is capable of depositing items directly into a spreadsheet. This code shows how to do that for your particular situation.
NEW_PERSON, ERROR_LINE = 1,2
def Line_items():
with open('katherine.txt') as katherine:
for line in katherine:
line = line.strip()
if not line:
continue
items = line.split()
if items[0].isnumeric():
yield NEW_PERSON, items
elif items[:2] == ['ERROR', 'NUM']:
yield ERROR_LINE, line
else:
continue
from openpyxl import Workbook
wb = Workbook()
ws = wb.active
ws['A2'] = 'REG NO'
ws['B2'] = 'LASTNAME'
ws['C2'] = 'FIRSTNAME'
ws['D2'] = 'ERROR'
row = 2
for kind, data in Line_items():
if kind == NEW_PERSON:
row += 2
ws['A{:d}'.format(row)] = int(data[0])
ws['B{:d}'.format(row)] = data[-2]
ws['C{:d}'.format(row)] = data[-1]
first = True
else:
if first:
first = False
else:
row += 1
ws['D{:d}'.format(row)] = data
wb.save(filename='katherine.xlsx')
This is a screen snapshot of the result.

Edit CSV file in python which reads values from another json file in python

I wanted to edit a csv file which reads the value from one of my another json file in python 2.7
my csv is : a.csv
a,b,c,d
,10,12,14
,11,14,15
my json file is a.json
{"a":20}
i want my where the column 'a' will try to match in json file. if their is a match. it should copy that value from json and paste it to my csv file and the final output of my csv file should be looks like this.
a,b,c,d
20,10,12,14
20,11,14,15
Till now I what I have tried is
fileCSV = open('a.csv', 'a')
fileJSON = open('a.json', 'r')
jsonData = fileJSON.json()
for k in range(jsonData):
for i in csvRow:
for j in jsonData.keys():
if i == j:
if self.count == 0:
self.data = jsonData[j]
self.count = 1
else:
self.data = self.data + "," + jsonData[j]
self.count = 0
fileCSV.write(self.data)
fileCSV.write("\n")
k += 1
fileCSV.close()
print("File created successfully")
I will be really thankful if anyone can help me for this.
please ignore any syntactical and indentation error.
Thank You.

Some basic string parsing will get you here.. I wrote a script which works for the simple scenario which you refer to.
check if this solves your problem:
import json
from collections import OrderedDict
def list_to_csv(listdat):
csv = ""
for val in listdat:
csv = csv+","+str(val)
return csv[1:]
lines = []
csvfile = "csvfile.csv"
outcsvfile = "outcsvfile.csv"
jsonfile = "jsonfile.json"
with open(csvfile, encoding='UTF-8') as a_file:
for line in a_file:
lines.append(line.strip())
columns = lines[0].split(",")
data = lines[1:]
whole_data = []
for row in data:
fields = row.split(",")
i = 0
rowData = OrderedDict()
for column in columns:
rowData[columns[i]] = fields[i]
i += 1
whole_data.append(rowData)
with open(jsonfile) as json_file:
jsondata = json.load(json_file)
keys = list(jsondata.keys())
for key in keys:
value = jsondata[key]
for each_row in whole_data:
each_row[key] = value
with open(outcsvfile, mode='w', encoding='UTF-8') as b_file:
b_file.write(list_to_csv(columns)+'\n')
for row_data in whole_data:
row_list = []
for ecolumn in columns:
row_list.append(row_data.get(ecolumn))
b_file.write(list_to_csv(row_list)+'\n')
CSV output is not written to the source file but to a different file.
The output file is also always truncated and written, hence the 'w' mode.

I would recommend using csv.DictReader and csv.DictWriter classes which will read into and out of python dicts. This would make it easier to modify the dict values that you read in from the JSON file.

extracting data from CSV file using a reference

I have a csv file with several hundred organism IDs and a second csv file with several thousand organism IDs and additional characteristics (taxonomic information, abundances per sample, etc)
I am trying to write a code that will extract the information from the larger csv using the smaller csv file as a reference. Meaning it will look at both smaller and larger files, and if the IDs are in both files, it will extract all the information form the larger file and write that in a new file (basically write the entire row for that ID).
so far I have written the following, and while the code does not error out on me, I get a blank file in the end and I don't exactly know why. I am a graduate student that knows some simple coding but I'm still very much a novice,
thank you
import sys
import csv
import os.path
SparCCnames=open(sys.argv[1],"rU")
OTU_table=open(sys.argv[2],"rU")
new_file=open(sys.argv[3],"w")
Sparcc_OTUs=csv.writer(new_file)
d=csv.DictReader(SparCCnames)
ids=csv.DictReader(OTU_table)
for record in ids:
idstopull=record["OTUid"]
if idstopull[0]=="OTUid":
continue
if idstopull[0] in d:
new_id.writerow[idstopull[0]]
SparCCnames.close()
OTU_table.close()
new_file.close()

I'm not sure what you're trying to do in your code but you can try this:
def csv_to_dict(csv_file_path):
csv_file = open(csv_file_path, 'rb')
csv_file.seek(0)
sniffdialect = csv.Sniffer().sniff(csv_file.read(10000), delimiters='\t,;')
csv_file.seek(0)
dict_reader = csv.DictReader(csv_file, dialect=sniffdialect)
csv_file.seek(0)
dict_data = []
for record in dict_reader:
dict_data.append(record)
csv_file.close()
return dict_data
def dict_to_csv(csv_file_path, dict_data):
csv_file = open(csv_file_path, 'wb')
writer = csv.writer(csv_file, dialect='excel')
headers = dict_data[0].keys()
writer.writerow(headers)
# headers must be the same with dat.keys()
for dat in dict_data:
line = []
for field in headers:
line.append(dat[field])
writer.writerow(line)
csv_file.close()
if __name__ == "__main__":
big_csv = csv_to_dict('/path/to/big_csv_file.csv')
small_csv = csv_to_dict('/path/to/small_csv_file.csv')
output = []
for s in small_csv:
for b in big_csv:
if s['id'] == b['id']:
output.append(b)
if output:
dict_to_csv('/path/to/output.csv', output)
else:
print "Nothing."
Hope that will help.

You need to read the data into a data structure, assuming OTUid is unique you can store this into a dictionary for fast lookup:
with open(sys.argv[1],"rU") as SparCCnames:
d = csv.DictReader(SparCCnames)
fieldnames = d.fieldnames
data = {i['OTUid']: i for i in d}
with open(sys.argv[2],"rU") as OTU_table, open(sys.argv[3],"w") as new_file:
Sparcc_OTUs = csv.DictWriter(new_file, fieldnames)
ids = csv.DictReader(OTU_table)
for record in ids:
if record['OTUid'] in data:
Sparcc_OTUs.writerow(data[record['OTUid']])

Thank you everyone for your help. I played with things and consulted with an advisor, and finally got a working script. I am posting it in case it helps someone else in the future.
Thanks!
import sys
import csv
input_file = csv.DictReader(open(sys.argv[1], "rU")) #has all info
ref_list = csv.DictReader(open(sys.argv[2], "rU")) #reference list
output_file = csv.DictWriter(
open(sys.argv[3], "w"), input_file.fieldnames) #to write output file with headers
output_file.writeheader() #write headers in output file
white_list={} #create empty dictionary
for record in ref_list: #for every line in my reference list
white_list[record["Sample_ID"]] = None #store into the dictionary the ID's as keys
for record in input_file: #for every line in my input file
record_id = record["Sample_ID"] #store ID's into variable record_id
if (record_id in white_list): #if the ID is in the reference list
output_file.writerow(record) #write the entire row into a new file
else: #if it is not in my reference list
continue #ignore it and continue iterating through the file

Large text file to csv, can't open text file

I'm trying to convert this 3,1 GB text file from https://snap.stanford.edu/data/
into a csv file. All the data is structured like:
name: something
age: something
gender: something
which makes it a pretty large text file with some million lines.
I have tried to write a py script to convert it but for some reason it won't read the lines in my for each loop.
Here is the code:
import csv
def trycast(x):
try:
return float(x)
except:
try:
return int(x)
except:
return x
cols = ['product_productId', 'review_userId', 'review_profileName', 'review_helpfulness', 'review_score', 'review_time', 'review_summary', 'review_text']
f = open("movies.txt", "wb")
w = csv.writer(f)
w.writerow(cols)
doc = {}
with open('movies.txt') as infile:
for line in infile:
line = line.strip()
if line=="":
w.writerow([doc.get(col) for col in cols])
doc = {}
else:
idx = line.find(":")
key, value = tuple([line[:idx], line[idx+1:]])
key = key.strip().replace("/", "_").lower()
value = value.strip()
doc[key] = trycast(value)
f.close()
I'm not sure if it is because the document is to large, because a regulare notepad program won't be able to open it.
Thanks up front! :-)

In the line f = open("movies.txt", "wb") you're opening the file for writing, and thereby deleting all its content. Later on, you're trying to read from that same file. It probably works fine if you change the output filename. (I am not going to download 3.1 GB to test it. ;) )

python text reading

datafile = open("temp.txt", "r")
record = datafile.readline()
while record != '':
d1 = datafile.strip("\n").split(",")
print d1[0],float (d1[1])
record = datafile.readline()
datafile.close()
The temp file contains
a,12.7
b,13.7
c,18.12
I can't get output. Please help.

The correct code should be:
with open('temp.txt') as f:
for line in f:
after_split = line.strip("\n").split(",")
print after_split[0], float(after_split[1])
The main reason you're not getting output in your code is that datafile doesn't have a strip() method, and I'm surprised you're not getting exceptions.
I highly suggest you read the Python tutorial - it looks like you're trying to write Python in another language and that is not A Good Thing

You want to call strip and split on the line, not the file.
Replace
d1 = datafile.strip("\n").split(",")
With
d1 = record.strip("\n").split(",")

you operating with file handler, but should work on line
like this d1 = record.strip("\n").split(",")
datafile = open("temp.txt", "r")
record = datafile.readline()
while record != '':
d1 = record.strip("\n").split(",")
print d1[0],float (d1[1])
record = datafile.readline()
datafile.close()

Perhaps the following will work better for you (comments as explanation):
# open file this way so that it automatically closes upon any errors
with open("temp.txt", "r") as f:
data = f.readlines()
for line in data:
# only process non-empty lines
if line.strip():
d1 = line.strip("\n").split(",")
print d1[0], float(d1[1])