csv

问题 I'm trying to figure out the best way to do this. I have a database with 5 tables around 5 records/rows in MySQL and I need to update it frequently. The problem is the file I upload will be csv file. Also I want each lines to go into 5 different tables.,I'm trying to updated 'where' there is a unique id. uid="001"; What is the best way to achieve this? I've been trying since morning, and I only know how to update one table alone at a time. Your suggestions is most appreciated. Thanks. sample

问题 I'm trying to figure out the best way to do this. I have a database with 5 tables around 5 records/rows in MySQL and I need to update it frequently. The problem is the file I upload will be csv file. Also I want each lines to go into 5 different tables.,I'm trying to updated 'where' there is a unique id. uid="001"; What is the best way to achieve this? I've been trying since morning, and I only know how to update one table alone at a time. Your suggestions is most appreciated. Thanks. sample

问题 I have a *.xlsm file which has 20 sheets in it. I want to save few sheets as *.csv (formatting loss is fine) individually. Already tried xlrd-xlwt and win32com libraries but could not get through. Can anybody please provide a code snippet which does the above processing in Python? I have other python dependencies so no other language would work. Thanks 回答1: xlrd should work fine on xlsm files as well. I tested the code with a random xlsm file, and it worked perfectly. import csv import xlrd

问题 I'm building a Django app that enables users to upload a CSV via a form using a FormField. Once the CSV is imported I use the Pandas read_csv(filename) command to read in the CSV so I can do some processing on the CSV using Pandas. I've recently started learning the really useful Dask library because the size of the uploaded files can be larger than memory. Everything works fine when using Pandas pd.read_csv(filename) but when I try and use Dask dd.read_csv(filename) I get the error "

问题 I'm building a Django app that enables users to upload a CSV via a form using a FormField. Once the CSV is imported I use the Pandas read_csv(filename) command to read in the CSV so I can do some processing on the CSV using Pandas. I've recently started learning the really useful Dask library because the size of the uploaded files can be larger than memory. Everything works fine when using Pandas pd.read_csv(filename) but when I try and use Dask dd.read_csv(filename) I get the error "

问题 I have a list of keyword to find from a list of file name. Example, if the keyword is 'U12' , I want to find the csv file that contain 'U12' which is 'h_ABC_U12.csv' and print it out. word = ['U12','U13','U14'] file_list = ['h_ABC_U12.csv','h_GGG_U13.csv','h_HVD_U14.csv','h_MMMB_U15.csv'] for x in range (len(word)): if word[x] in file_list: #print the file name This is part of the code but unable to continue after some searches. I need the full name that match the word to print out. 回答1: I

问题 I have a list of keyword to find from a list of file name. Example, if the keyword is 'U12' , I want to find the csv file that contain 'U12' which is 'h_ABC_U12.csv' and print it out. word = ['U12','U13','U14'] file_list = ['h_ABC_U12.csv','h_GGG_U13.csv','h_HVD_U14.csv','h_MMMB_U15.csv'] for x in range (len(word)): if word[x] in file_list: #print the file name This is part of the code but unable to continue after some searches. I need the full name that match the word to print out. 回答1: I

问题 I'm trying to work with a CSV file that is essentially a database of records. On load of the game I Read in a record and instantiate a prefab button, one at a time with the correct text from the CSV file. It's not always the case that the index of the button will be the same as the index of the record where I got the information in the CSV file. So far I setup a Save function that I want certain records that have changed based on a tricks "name" field to reflect in the CSV file. What would be

问题 I've been searching for a way to concatenate my Excel (or any other tool/software handling tables) rows based on common cells. As an example: I have this tab-stop divided table. Each of the values is in a separate row: angeb* 12 16 18 zyste* 60 61 zynisch* 12 zyste* 60 abstreit* 70 anflunker* 70 angeb* 70 I want to concatenate the rows in a way that the result would be: angeb* 12 16 18 70 zyste* 60 61 zynisch* 12 abstreit* 70 anflunker* 70 It does work by doing as proposed in this tutorial,

问题 I want to do something like: import csv import tornado.web class MainHandler(tornado.web.RequestHandler): def post(self): uploaded_csv_file = self.request.files['file'][0] with uploaded_csv_file as csv_file: for row in csv.reader(csv_file): self.write(' , '.join(row)) But, uploaded_csv_file is not of type file . What is the best practice here? Sources: http://docs.python.org/2/library/csv.html http://docs.python.org/2/library/functions.html#open https://stackoverflow.com/a/11911972/242933 回答1