I have got a file with the following lines
{"status":"OK","message":"OK","data":[{"type":"addressAccessType","addressAccessId":"0a3f508f-e7c8-32b8-e044-0003ba298018","municipalityCode":"0766","municipalityName":"Hedensted","streetCode":"0072","streetName":"Værnegården","streetBuildingIdentifier":"13","mailDeliverySublocationIdentifier":"","districtSubDivisionIdentifier":"","postCodeIdentifier":"8000","districtName":"Århus","presentationString":"Værnegården 13, 8000 Århus","addressSpecificCount":1,"validCoordinates":true,"geometryWkt":"POINT(553564 6179299)","x":553564,"y":6179299}]}
I want to transform every line into a csv readable file with headers. Like the following
status,message,data,addressAccessId,municipalityCode,municipalityName,streetCode,streetName,streetBuildingIdentifier,mailDeliverySublocationIdentifier,districtSubDivisionIdentifier,postCodeIdentifier,districtName,presentationString,addressSpecificCount,validCoordinates,geometryWkt,x,y
OK,OK,data:type,addressAccessType,0a3f508f-e7c8-32b8-e044-0003ba298018,0766,Hedensted,0072,Værnegården,13,,,8000,Århus,Værnegården 13, 8000 Århus,1,true,POINT553564 6179299,553564,6179299
How do I accomplish that? Code and explanation are very welcome. So far this is what I have come up with the following from this example:(How can I convert JSON to CSV?)
x = json.loads(x)
f = csv.writer(open('test.csv', 'wb+'))
# Write CSV Header, If you dont need that, remove this line
f.writerow(['status', 'message', 'type', 'addressAccessId', 'municipalityCode','municipalityName','streetCode','streetName','streetBuildingIdentifier','mailDeliverySublocationIdentifier','districtSubDivisionIdentifier','postCodeIdentifier','districtName','presentationString','addressSpecificCount','validCoordinates','geometryWkt','x','y'])
for x in x:
f.writerow([x['status'],
x['message'],
x['data']['type'],
x['data']['addressAccessId'],
x['data']['municipalityCode'],
x['data']['municipalityName'],
x['data']['streetCode'],
x['data']['streetName'],
x['data']['streetBuildingIdentifier'],
x['data']['mailDeliverySublocationIdentifier'],
x['data']['districtSubDivisionIdentifier'],
x['data']['postCodeIdentifier'],
x['data']['districtName'],
x['data']['presentationString'],
x['data']['addressSpecificCount'],
x['data']['validCoordinates'],
x['data']['geometryWkt'],
x['data']['x'],
x['data']['y']])
I have looked through and tried a lot of other solutions, including DictWriter, replace() and translate() to remove characthers but have not yet been able to transform the line to my need. The purpose being able to select the fields that are output into a new file, and transforming x and y to a new coordinate system. But for now Im just trying to parse the above line to a csv file. Can anyone offer code and explanation of their code? Thank you very much for your time.
Below are the first few lines of my addresses.txt
{"status":"OK","message":"OK","data":[{"type":"addressAccessType","addressAccessId":"0a3f5081-e039-32b8-e044-0003ba298018","municipalityCode":"0265","municipalityName":"Roskilde","streetCode":"0831","streetName":"Brønsager","streetBuildingIdentifier":"69","mailDeliverySublocationIdentifier":"","districtSubDivisionIdentifier":"Svogerslev","postCodeIdentifier":"4000","districtName":"Roskilde","presentationString":"Brønsager 69, 4000 Roskilde","addressSpecificCount":1,"validCoordinates":true,"geometryWkt":"POINT(690026 6169309)","x":690026,"y":6169309}]}
{"status":"OK","message":"OK","data":[{"type":"addressAccessType","addressAccessId":"0a3f5089-ecab-32b8-e044-0003ba298018","municipalityCode":"0461","municipalityName":"Odense","streetCode":"9505","streetName":"Vægtens Kvarter","streetBuildingIdentifier":"271","mailDeliverySublocationIdentifier":"","districtSubDivisionIdentifier":"Holluf Pile","postCodeIdentifier":"5220","districtName":"Odense SØ","presentationString":"Vægtens Kvarter 271, 5220 Odense SØ","addressSpecificCount":1,"validCoordinates":true,"geometryWkt":"POINT(592191 6135829)","x":592191,"y":6135829}]}
{"status":"OK","message":"OK","data":[{"type":"addressAccessType","addressAccessId":"0a3f507c-adc3-32b8-e044-0003ba298018","municipalityCode":"0165","municipalityName":"Albertslund","streetCode":"0445","streetName":"Skyttehusene","streetBuildingIdentifier":"33","mailDeliverySublocationIdentifier":"","districtSubDivisionIdentifier":"","postCodeIdentifier":"2620","districtName":"Albertslund","presentationString":"Skyttehusene 33, 2620 Albertslund","addressSpecificCount":1,"validCoordinates":true,"geometryWkt":"POINT(711079 6174741)","x":711079,"y":6174741}]}
{"status":"OK","message":"OK","data":[{"type":"addressAccessType","addressAccessId":"0a3f509c-7f57-32b8-e044-0003ba298018","municipalityCode":"0851","municipalityName":"Aalborg","streetCode":"5205","streetName":"Løvstikkevej","streetBuildingIdentifier":"36","mailDeliverySublocationIdentifier":"","districtSubDivisionIdentifier":"","postCodeIdentifier":"9000","districtName":"Aalborg","presentationString":"Løvstikkevej 36, 9000 Aalborg","addressSpecificCount":1,"validCoordinates":true,"geometryWkt":"POINT(552407 6322490)","x":552407,"y":6322490}]}
{"status":"OK","message":"OK","data":[{"type":"addressAccessType","addressAccessId":"0a3f5098-32a6-32b8-e044-0003ba298018","municipalityCode":"0779","municipalityName":"Skive","streetCode":"0462","streetName":"Landevejen","streetBuildingIdentifier":"52","mailDeliverySublocationIdentifier":"","districtSubDivisionIdentifier":"Håsum","postCodeIdentifier":"7860","districtName":"Spøttrup","presentationString":"Landevejen 52, 7860 Spøttrup","addressSpecificCount":1,"validCoordinates":true,"geometryWkt":"POINT(491515 6269739)","x":491515,"y":6269739}]}
Note that the data key holds a list of dictionaries. x['data']['type'] wouldn't work, but x['data'][0]['type'] would. There might be more than one such dictionary in that list, however. I'll assume you want a CSV row per x['data'] dictionary.
Next, it appears you have a UTF-8 BOM on every line; whatever wrote this was not using UTF-8 encoding correctly. We need to strip this marker, the first 3 characters.
Last, JSON strings are always Unicode data, and you have non-ASCII characters in your data, so you'll have to encode to bytestrings again before passing the data to the CSV writer object.
I'd use csv.DictWriter here, with a pre-defined list of field names:
import codecs
import csv
import json
fields = [
'status', 'message', 'type', 'addressAccessId', 'municipalityCode',
'municipalityName', 'streetCode', 'streetName', 'streetBuildingIdentifier',
'mailDeliverySublocationIdentifier', 'districtSubDivisionIdentifier',
'postCodeIdentifier', 'districtName', 'presentationString', 'addressSpecificCount',
'validCoordinates', 'geometryWkt', 'x', 'y']
with open('test.csv', 'wb') as csvfile, open('jsonfile', 'r') as jsonfile:
writer = csv.DictWriter(csvfile, fields)
writer.writeheader()
for line in jsonfile:
if line.startswith(codecs.BOM_UTF8):
line = line[3:]
entry = json.loads(line)
for item in entry['data']:
row = dict(item, status=entry['status'], message=entry['message'])
row = {k.encode('utf8'): unicode(v).encode('utf8') for k, v in row.iteritems()}
writer.writerow(row)
The row dictionary is basically a copy of each of the dictionaries in the entry['data'] list, with the status and message keys copied over separately. This makes row a flat dictionary instead.
I also read your input file line by line, as you say that each line contains a separate JSON entry.
Open the output file with cvs.DictWriter() and define the output header fields as you specified. Use extrasaction='ignore' and restval='' as options.
Look at Opening A large JSON file in Python with no newlines for csv conversion Python 2.6.6 for help with processing large files as I had a similar question Also look at the question that I link to.
I build a similar type of system from a JSON using appropriate loops.
for example,
def parse_row(currdata):
outx = {}
# currdata is defined earlier to point to the x['data'] dictionary
for eachx in currdata:
outx[eachx] = currdata[eachx]
return outx
where this is in a function with currdata as an argument and called with x['data'][row] as the input argument.
rows = len(x['data'])
for row in range(rows):
outx = parse_row(x['data'][row])
# process the row and create output
This should allow you to set up the parsing properly. I cannot copy the actual code into this answer but this should point you to a solution.
For each user I have the list of events in which he participated.
e.g. bob : [event1,event2,...]
I want to write it in csv file. I created a dictionary (key - user & value - list of events)
I wrote it in csv. The following is the sample output
username, frnds
"abc" ['event1','event2']
where username is first col and frnds 2nd col
This is code
writer = csv.writer(open('eventlist.csv', 'ab'))
for key, value in evnt_list.items():
writer.writerow([key, value])
when I am reading the csv I am not getting the list directly. But I am getting it in following way
['e','v','e','n','t','1','','...]
I also tried to write the list directly in csv but while reading am getting the same output.
What I want is multiple values in a single cell so that when I read a column for a row I get list of all events.
e.g
colA colB
user1,event1,event2,...
I think it's not difficult but somehow I am not getting it.
###Reading
I am reading it with the help of following
codereader = csv.reader(open("eventlist.csv"))
reader.next()
for row in reader:
tmp=row[1]
print tmp # it is printing the whole list but
print tmp[0] #the output is [
print tmp[1] #output is 'e' it should have been 'event1'
print tmp[2] #output is 'v' it should have been 'event2'
you have to format your values into a single string:
with open('eventlist.csv', 'ab') as f:
writer = csv.writer(f, delimiter=' ')
for key, value in evnt_list.items():
writer.writerow([key, ','.join(value)])
exports as
key1 val11,val12,val13
key2 val21,val22,val23
READING: Here you have to keep in mind, that you converted your Python list into a formatted string. Therefore you cannot use standard csv tools to read it:
with open("eventlist.csv") as f:
csvr = csv.reader(f, delimiter=' ')
csvr.next()
for rec in csvr:
key, values_txt = rec
values = values_txt.split(',')
print key, values
works as awaited.
You seem to be saying that your evnt_list is a dictionary whose keys are strings and whose values are lists of strings. If so, then the CSV-writing code you've given in your question will write a string representation of a Python list into the second column. When you read anything in from CSV, it will just be a string, so once again you'll have a string representation of your list. For example, if you have a cell that contains "['event1', 'event2']" you will be reading in a string whose first character (at position 0) is [, second character is ', third character is e, etc. (I don't think your tmp[1] is right; I think it is really ', not e.)
It sounds like you want to reconstruct the Python object, in this case a list of strings. To do that, use ast.literal_eval:
import ast
cell_string_value = "['event1', 'event2']"
cell_object = ast.literal_eval(cell_string_value)
Incidentally, the reason to use ast.literal_eval instead of just eval is safety. eval allows arbitrary Python expressions and is thus a security risk.
Also, what is the purpose of the CSV, if you want to get the list back as a list? Will people be reading it (in Excel or something)? If not, then you may want to simply save the evnt_list object using pickle or json, and not bother with the CSV at all.
Edit: I should have read more carefully; the data from evnt_list is being appended to the CSV, and neither pickle nor json is easily appendable. So I suppose CSV is a reasonable and lightweight way to accumulate the data. A full-blown database might be better, but that would not be as lightweight.
I am trying to find the min and max out of a csv file, and have it output into a text file, currently my code outputs all data into the output file, and I am unsure of how to grab the data out of the multiple columns and have them sorted accordingly.
Any guidance would be appreciated, as I don't have a good lead on how to figure this out
read_file = open("riskfactors.csv", 'r')
def create_file():
read_file = open("riskfactors.csv", 'r')
write_file = open("best_and_worst.txt", "w")
for line_str in read_file:
read_file.readline()
print (line_str,file=write_file)
write_file.close()
read_file.close()
Assuming your file is a standard .csv file containing only numbers separated by semicolons:
1;5;7;6;
3;8;1;1;
Then it's easiest to use the str.split() command, followed by a type conversion to int.
You could store all values in a list (or quicker: set) and then get the maximum:
valuelist=[]
for line_str in read_file:
for cell in line_str.split(";"):
valuelist.append(int(cell))
print(max(valuelist))
print(min(valuelist))
Warning: If your file contains non-number entries you'd have to filter them out. .csv-files can also have different delimiters.
import sys, csv
def cmp_risks(x, y):
# This assumes risk factors are prioritised by key columns 1, 3
# and that column 1 is numeric while column 3 is textual
return cmp(int(x[0]), int(y[0])) or cmp(x[2], y[2])
l = sorted(csv.reader(sys.stdin), cmp_risks))
# Write out the first and last rows
csv.writer(sys.stdout).writerows([l[0], l[len(l)-1]])
Now, I took a shortcut and said the input and output files were sys.stdin and sys.stdout. You'd probably replace these with the file objects you created in your original question. (e.g. read_file and write_file)
However, in my case, I'd probably just run it (if I were using linux) with:
$ ./foo.py <riskfactors.csv >best_and_worst.txt