input :csv1,csv2,csv3
output :sheet1,sheet2,sheet3 etc in one xlxs file.
Any possible suggestion in python and unix shell script is helpful.
Thanks In advance.
Related
I have made a few corrections to location names in a GeoLite2 CSV file.
My site only retrieves locations from the MMDB file, so how can I compile back the changed CSV file into the MMDB binary again.
I searched everywhere for a solution but can't find it.
Thanks for any tip.
Carlos
Currently there are only 2 open source MMDB file writers:
MaxMind::DB::Writer (Perl language)
Go MaxMind DB Writer (Go language)
The second one unfortunately has only a subset of the features available for the Perl one, but it should be enough for writing a program that creates the MMDB file reading line by line the CSV one and creating the mmdbtype instances.
You can check out our mmdbctl utility tool.
To convert a CSV file to an MMDB file use the import command:
$ mmdbctl import --in data.csv --out data.mmdb
Instructions, features, and documentation are available here: github.com/ipinfo/mmdbctl.
Right now it only supports string data types, and not nested data types. See this issue for more information.
I am not able to figure out the precise functions in GCP Dataflow Python SDK that read from and write to csv files (or any non-txt files for that matter). For BigQuery, I have figured out the following functions:
beam.io.Read(beam.io.BigQuerySource('%Table_ID%'))
beam.io.Write(beam.io.BigQuerySink('%Table_ID%'))
For reading textfiles, the ReadFromText and WriteToText functions are known to me.
However, I am not able to find any examples for GCP Dataflow Python SDK in which data is written to or read from csv files. Please could you provide the GCP Dataflow Python SDK functions for reading from and writing to csv files in the same manner as I have done for the functions relating to BigQuery above?
There is a CsvFileSource in the beam_utils PyPi package repository, that reads .csv files, deals with file headers, and can set custom delimiters. More information on how to use this source in this answer. Hope that helps!
CSV files are text files. The simplest (though somewhat inelegant) way of reading them would be to do a ReadFromText, and then split the lines read on the commas (e.g. beam.Map(lambda x: x.split(','))).
For the more elegant option, check out this question, or simply use the beam_utils pip repository and use the beam_utils.sources.CsvFileSource source to read from.
Currently I'm just saving the file as MS-DOS CSV with excel. I'm looking for the fastest way (in terms of writing the code) of doing it automatically.
I strongly prefer C++, but any simple executable program I can call from a C++ app would do.
Unzip the xslx file with eg WinZip and have a look at the resulting files. This may help.
I tried to build a chatbot in AIML. I downloaded the codes from http://nlp-addiction.com/chatbot/mathbot/ but couldn't get the idea about how to run the program. Please help me.
An AIML file isn't program code, it's a data file (much like any other xml file).
You need to use an interpreter like Program-AB to load and use the file to answer queries.
If you just want to test the contents and formatting of the aiml file, you could use Pandorabots and load the file into a blank bot fairly easily.
Yes, AIML file isn't program code. It's just like a data format. You can learn about it more from here : http://www.alicebot.org/aiml.html
AIML is a data encoding format that tells the bot when to do what to do. Many interpreters can be used to interpret the aiml tags.
One of them is PyAIML which is python based interpreter fairly simple to use.
There are gov't data files: http://www.cdc.gov/EpiInfo/
Available in this weird SAS format. How can I convert them into XML/CSV, something much simpler that can be read by scripts/etc.???
I had the same problem, so i made a simple SAS data viewer. You download it from the downloads section here: http://code.google.com/p/sasquatch
It has alot of the same features as SAS Universal Viewer, but its still a work in progress.
You need to have Adobe AIR installed, you can get that on the adobe website.
Are the data in the SAS XPORT (.xpt) or .sas7bdat format?
For future reference, SAS XPORT files can be read and written using the 'SASxport' package for R (http://cran.r-project.org/web/packages/SASxport/index.html).
(Already posted this to superuser.com)
SAS Institute (the company that makes SAS) produces a viewer for SAS data sets.
Note that SAS program files usually have the extension .sas, whereas the data files themselves usually have the extension .sas7bdat.
(EDIT: I notice belatedly that your title says on a Mac, so this may not help much as I believe the tool is Windows only.)
Here a quick-and-dirty python five-liner to convert a SAS .xpt (aka XPORT) file to .csv
import pandas as pd
FILE_PATH = "(fully qualified name of directory containing file)"
FILE = "ABC" # filename itself (without suffix)
# Note: might need to substitute the column name of the index (in quotes) for "None" here
df = pd.read_sas(FILE_PATH + FILE + '.XPT', index=None)
df.to_csv(FILE_PATH + FILE + '.csv')
Hopefully this might help someone
JMP runs on MAC and can read sas files. Visit jmp.com for more information.
There are two parts to your question
1. Read these files
2. Convert these files
I looked into the link you shared there are no directly downloadable files, but I am assuming that you mean the files for windows.
For viewing you can use the folloiwng
a. SAS Universal viewer: https://support.sas.com/downloads/package.htm?pid=667
b. Use SAS on mac to directly read the files
For conversion you can do the following
a. Use SAS proc import to export and proc export to export the files feature,
b. Use third party softwares, e.g., DBMSCopy for this;
c. Download trial version of JMP and convert the files to desired format, e.g., CSV/txt etc and get done with it.