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Sebastian Raschka
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reorganized Readme
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‎README.md‎

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Useful functions, tutorials, and other Python-related things
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###Links to view the IPython Notebooks
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- [Python benchmarks via `timeit`](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/benchmarks/timeit_tests.ipynb?create=1)
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- [Implementing the least squares fit method for linear regression and speeding it up via Cython](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/benchmarks/cython_least_squares.ipynb?create=1)
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- [Benchmarks of different palindrome functions](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/benchmarks/palindrome_timeit.ipynb?create=1)
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- [A collection of not so obvious Python stuff you should know!](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/not_so_obvious_python_stuff.ipynb?create=1)
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- [Python's scope resolution for variable names and the LEGB rule](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/scope_resolution_legb_rule.ipynb?create=1)
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- [Happy Mother's Day](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/funstuff/happy_mothers_day.ipynb?create=1)
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### Links to Markdown files
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- [A thorough guide to SQLite database operations in Python](./sqlite3_howto/README.md)
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- [Unit testing in Python - Why we want to make it a habit](./tutorials/unit_testing.md)
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- [Installing Scientific Packages for Python3 on MacOS 10.9 Mavericks](./tutorials/installing_scientific_packages.md)
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###Links to view the IPython Notebooks and Markdown files
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<br>
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<br>
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<br>
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**// Python tips and tutorials**
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- A collection of not so obvious Python stuff you should know! [[IPython nb]](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/not_so_obvious_python_stuff.ipynb?create=1)
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- Python's scope resolution for variable names and the LEGB rule [[IPython nb]](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/scope_resolution_legb_rule.ipynb?create=1)
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- A thorough guide to SQLite database operations in Python [[Markdown]](./sqlite3_howto/README.md)
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- Unit testing in Python - Why we want to make it a habit [[Markdown]](./tutorials/unit_testing.md)
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- Installing Scientific Packages for Python3 on MacOS 10.9 Mavericks [[Markdown]](./tutorials/installing_scientific_packages.md)
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**// benchmarks**
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- Python benchmarks via `timeit` [[IPython nb]](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/benchmarks/timeit_tests.ipynb?create=1)
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- Implementing the least squares fit method for linear regression and speeding it up via Cython [[IPython nb]](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/benchmarks/cython_least_squares.ipynb?create=1)
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- Benchmarks of different palindrome functions [[IPython nb]](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/benchmarks/palindrome_timeit.ipynb?create=1)
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**// other**
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- Happy Mother's Day [[IPython nb]](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/funstuff/happy_mothers_day.ipynb?create=1)
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**// useful snippets**
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- convert 'tab-delimited' to 'comma-separated' CSV files [[IPython nb]](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/useful_scripts/fix_tab_csv.ipynb?create=1)

‎useful_scripts/fix_tab_csv.ipynb‎

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{
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"metadata": {
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"name": "",
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"signature": "sha256:996358a25da6fc77c66d183e79209307af06bd2f9abb0656d3bb70cfc2fe597a"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"worksheets": [
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Sebastian Raschka 05/09/2014"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Fixing CSV files"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"We have a directory `../CSV_files_raw/` with CSV files where some of them have 'tab-separated' and some of them 'comma-separated' columns. \n",
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"Here, we will 'fix' them, i.e., have them all comma-separated, and save them to a new directory `../CSV_fixed`."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"First, we create a dictionary with the file basenames as keys. The values are lists of the file paths to the raw and new fixed CSV files. e.g., \n",
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"\n",
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" {\n",
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" 'abc.csv': ['../CSV_files_raw/abc.csv', '../CSV_fixed/abc.csv'], \n",
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" 'def.csv': ['../CSV_files_raw/def.csv', '../CSV_fixed/def.csv'], \n",
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" ...\n",
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" }"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"import sys\n",
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"import os\n",
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"\n",
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"raw_dir = '../CSV_files_raw/'\n",
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"fixed_dir = '../CSV_fixed'\n",
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"\n",
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"if not os.path.exists(fixed_dir):\n",
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" os.mkdir(fixed_dir)\n",
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"\n",
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"f_dict = {os.path.basename(f):[os.path.join(raw_dir, f),\n",
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" os.path.join(fixed_dir, f)]\n",
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" for f in os.listdir(raw_dir) if f.endswith('.csv')} "
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 8
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now, we can replace the tabs with commas for the new files very easily:"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"for f in f_dict.keys():\n",
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" with open(f_dict[f][0], 'r') as raw, open(f_dict[f][1], 'w') as fixed:\n",
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" for line in raw:\n",
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" line = line.strip().split('\\t')\n",
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" fixed.write(','.join(line) + '\\n')"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 11
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}
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],
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"metadata": {}
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}
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]
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}

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