accessnew...@gmail.com wrote:
> My current Test_Sort.csv looks like this (which constantly
> changes-although never more than 4 records, thus far anyway):
>
> RecNo,Count,District,Fruit,StoreNo
> 1,100,0,oranges,1254
> 2,30,3,apples,654
> 3,100,0,bananas,21
> 4,0,4,grapes,478
>
> I wrote the following python 2.7 script (stuck with 2.7)
>
> ---------------------
> import sys
> import csv
> import operator
>
>
> source = "E:\\Data\\Test_Sort.csv"
> result = "E:\\Data\\Test_Sort1.csv"
>
> with open(source,"rb") as source:
> rdr= csv.reader( source )
> with open(result,"wb") as result:
> next(rdr, None) # Skip header
> wtr= csv.writer( result )
> for r in rdr:
> wtr.writerow( (r[2], r[3])) # Only write columns 3 and 4 to a
> csv file
> exit
> exit
>
> data = csv.reader(open("E:\\Data\\Test_Sort1.csv"),delimiter=',')
> sortedlist = sorted(data, key=operator.itemgetter(0,1)) # sort by column
> 1, the 2 print sortedlist
>
> -----------------------------
>
> My sortedlist results are:
>
> [['0', 'bananas'], ['0', 'oranges'], ['3', 'apples'], ['4', 'grapes']]
>
> I want to output all fruits with the same District number out to a csv
> file called by its District number. (No headers)
>
> Thus in above example I would ultimately have three csv files:
>
> 0.csv
> bananas
> oranges
>
> 3.csv
> apples
>
> 4.csv
> grapes
>
> Question is : Any ideas as to how export this sortedlist to the tables
> described above?
The standard library offers itertools.groupby()
for district, group in itertools.groupby(
sortedlist, key=operator.itemgetter(0)):
with open(district + ".csv", "wb") as outfile:
csv.writer(outfile).writerows(group)
If you want try to do it by hand as an exercise -- you need a variable to
keep track of the current district:
last_district = None
for row in sortedlist:
district = row[0]
if last_district != district:
# open new file/writer
last_district = district
# write row
> I already have a script that already will look at each file and count the
> number of lines and insert the correct number of commas and the word "and"
> where appropriate in a sentence.
>
> My ultimate goal is to read each file and print out a sentence based on
> whether it has record or not, and if so how many records and then add the
> word "and" and/or commas between records if greater than 1. I will then
> concatenate all the sentences together to form a paragraph.
>
> Thus, the above example would say:
>
> The western district sold bananas and oranges. The central district sold
> apples. The southern district sold grapes.
Have a look at str.join():
>>> colors = ["red", "yellow", "blue"]
>>> print "Who's afraid of {}, and {}?".format(", ".join(colors[:-1]),
colors[-1])
Who's afraid of red, yellow, and blue?
> or if the files were:
>
> 0.csv
> apples
> bananas
> oranges
>
> 2.csv
> grapes
>
> The resulting paragraph would read:
>
> The western district sold apples, bananas, and oranges. The eastern
> district sold grapes.
>
> It may seem like a crazy way about getting my results but it was the best
> I could come up with given my limited knowledge of python.
No, it is what experienced programmers do all the time -- break a complex
task into manageable steps, come up with a simple solution for each step,
and then improve these steps as needed.
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