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PHP code to convert a MySQL query to CSV [closed]
What is the most efficient way to convert a MySQL query to CSV in PHP please?
6 Answers
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Are there any CSV readers/writer libraries in C#? [closed]
Are there any CSV readers/writer libraries in C#?
5 Answers
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Command line CSV viewer? [closed]
Anyone know of a command-line CSV viewer for Linux/OS X? I'm thinking of something like less but that spaces out the columns in a more readable way. (I'd be fine with opening it with OpenOffice Calc or Excel, but that's way too overpowered for just looking at the data like I need to.) Having ...
How to export data as CSV format from SQL Server using sqlcmd?
... -d myDB -E -Q "select col1, col2, col3 from SomeTable"
-o "MyData.csv" -h-1 -s"," -w 700
-h-1 removes column name headers from the result
-s"," sets the column seperator to ,
-w 700 sets the row width to 700 chars (this will need to be as wide as the longest row or it will wrap to the n...
Easy way to turn JavaScript array into comma-separated list?
...work out for themselves. OP asked for a comma-separated list, not a quoted CSV-type format.
– Wayne
Feb 10 '12 at 22:37
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'Incomplete final line' warning when trying to read a .csv file into R
I'm trying to read a .csv file into R and upon using this formula:
15 Answers
15
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How to parse a CSV file in Bash?
I'm working on a long Bash script. I want to read cells from a CSV file into Bash variables. I can parse lines and the first column, but not any other column. Here's my code so far:
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Best timestamp format for CSV/Excel?
I'm writing a CSV file. I need to write timestamps that are accurate at least to the second, and preferably to the millisecond. What's the best format for timestamps in a CSV file such that they can be parsed accurately and unambiguously by Excel with minimal user intervention?
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Skip the headers when editing a csv file using Python
I am using below referred code to edit a csv using Python. Functions called in the code form upper part of the code.
3 Ans...
Large, persistent DataFrame in pandas
...ldn't run out of memory, but there are currently memory problems with read_csv on large files caused by some complex Python internal issues (this is vague but it's been known for a long time: http://github.com/pydata/pandas/issues/407).
At the moment there isn't a perfect solution (here's a tediou...