# csv_to_xls
<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->
## Install
``` sh
pip install csv_to_xls
```
## How to use
When you install `csv_to_xls` you will get a cli tool named `csv2xls`:
``` python
!csv2xls --help
```
usage: csv2xls [-h] [--file_glob FILE_GLOB] [--out_file OUT_FILE] [--recursive]
[--delimiter DELIMITER] [--quotechar QUOTECHAR] [--symlinks]
[--file_re FILE_RE] [--folder_re FOLDER_RE]
[--skip_file_glob SKIP_FILE_GLOB] [--skip_file_re SKIP_FILE_RE]
[--skip_folder_re SKIP_FOLDER_RE]
path
Convert csv file(s) into an excel file, if multiple csvs put on tabs.
positional arguments:
path path to searching for *.csv files
optional arguments:
-h, --help show this help message and exit
--file_glob FILE_GLOB Only include files matching glob (default:
*.csv)
--out_file OUT_FILE output excel file (default: output.xlsx)
--recursive search subfolders (default: False)
--delimiter DELIMITER delimiter to use (default: ,)
--quotechar QUOTECHAR quote character to escape the delimiter
(default: ")
--symlinks follow symlinks? (default: False)
--file_re FILE_RE Only include files matching regex
--folder_re FOLDER_RE Only enter folders matching regex
--skip_file_glob SKIP_FILE_GLOB Skip files matching glob
--skip_file_re SKIP_FILE_RE Skip files matching regex
--skip_folder_re SKIP_FOLDER_RE Skip folders matching regex,
## Example
Consider the below csv files:
``` python
!ls _tests/
```
addresses.csv biostats.csv faithful.csv hw_200.csv tally_cab.csv
To merge these csvs into one excel file named `merged.xlsx`:
``` python
!csv2xls _tests/ --out_file merged.xlsx
```
We can see there is a worksheet for each filename:
``` python
import pandas as pd
pd.ExcelFile('merged.xlsx').sheet_names
```
['addresses', 'biostats', 'hw_200', 'tally_cab', 'faithful']
Let’s say we want to skip the `biostats.csv` file, we can use the
`--skip_file_re` arg:
``` python
!rm -f merged.xlsx
!csv2xls _tests/ --out_file merged.xlsx --skip_file_re 'biostats*'
```
Now that particular sheet is not there:
``` python
pd.ExcelFile('merged.xlsx').sheet_names
```
['addresses', 'hw_200', 'tally_cab', 'faithful']
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