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cannot download, $GOPATH not set
I want to install json2csv using go get github.com/jehiah/json2csv but I receive this error:
15 Answers
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How to create CSV Excel file C#? [closed]
I'm looking for a class for creating CSV Excel files.
13 Answers
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Pickle or json?
... answered Feb 13 '10 at 22:22
Håvard SHåvard S
20.4k55 gold badges5555 silver badges6767 bronze badges
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invalid byte sequence for encoding “UTF8”
... to help others and the search engines: this works for converting a Stripe CSV export with unreadable characters back into UTF-8: ` iconv -f ISO-8859-15 -t utf-8 customers.csv > customers-utf8.csv`
– sscarduzio
Nov 27 '17 at 21:49
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Import and Export Excel - What is the best library? [closed]
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I'm going to throw my hand in for flat csv files, if only because you've got the greatest control over the code. Just make sure that you read in the rows and process them one at a time (reading the document to the end and splitting will eat up all of your memory -...
CSS '>' selector; what is it? [duplicate]
...ered Dec 16 '10 at 10:44
David MårtenssonDavid Mårtensson
7,10044 gold badges2727 silver badges4646 bronze badges
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How to use the CSV MIME-type?
In a web application I am working on, the user can click on a link to a CSV file. There is no header set for the mime-type, so the browser just renders it as text. I would like for this file to be sent as a .csv file, so the user can directly open it with calc, excel, gnumeric, etc.
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How to read a .xlsx file using the pandas Library in iPython?
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DataFrame's read_excel method is like read_csv method:
dfs = pd.read_excel(xlsx_file, sheetname="sheet1")
Help on function read_excel in module pandas.io.excel:
read_excel(io, sheetname=0, header=0, skiprows=None, skip_footer=0, index_col=None, names=None, parse_c...
Read a zipped file as a pandas DataFrame
I'm trying to unzip a csv file and pass it into pandas so I can work on the file.
The code I have tried so far is:
5 Ans...
How to estimate how much memory a Pandas' DataFrame will need?
I have been wondering... If I am reading, say, a 400MB csv file into a pandas dataframe (using read_csv or read_table), is there any way to guesstimate how much memory this will need? Just trying to get a better feel of data frames and memory...
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