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added conversion to float · philouvb/python_reference@ed0eb89 · GitHub

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added conversion to float
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‎tutorials/sorting_csvs.ipynb‎

Lines changed: 90 additions & 12 deletions
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{
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"metadata": {
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"name": "",
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"signature": "sha256:683cfd7e6b5fd1dca9cd2028b294ec8ae44a175b613eb3c037d365a28957a987"
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"signature": "sha256:13c10e46fea51bcbbf203261897bb4d8ea2087e39925e077d452778f78d62b1e"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"## Sections\n",
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"- [Reading in a CSV file](#reading)\n",
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"- [Printing the CSV file contents](#printing)\n",
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"- [Converting numeric cells to floats](#floats)\n",
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"- [Sorting the CSV file](#sorting)\n",
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"- [Marking min/max values in particular columns](#marking)\n",
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"- [Writing out the modified table to as a new CSV file](#writing)\n",
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 1
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"prompt_number": 4
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},
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{
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"cell_type": "code",
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]
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}
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],
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"prompt_number": 3
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"prompt_number": 5
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},
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{
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"cell_type": "markdown",
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 4
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"prompt_number": 6
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},
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{
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"cell_type": "code",
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]
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}
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],
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"prompt_number": 5
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"prompt_number": 7
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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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"<a name='floats'></a>\n",
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"<br>\n",
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"<br>"
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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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"## Converting numeric cells to floats"
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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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"To avoid problems with the sorting approach that can occur when we have negative values in some cells, let us define a function that converts all numeric cells into float values."
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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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"def convert_cells_to_floats(csv_cont):\n",
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" \"\"\" \n",
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" Converts cells to floats if possible\n",
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" (modifies input CSV content list).\n",
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" \n",
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" \"\"\"\n",
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" for row in range(len(csv_cont)):\n",
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" for cell in range(len(csv_cont[row])):\n",
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" try:\n",
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" csv_cont[row][cell] = float(csv_cont[row][cell])\n",
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" except ValueError:\n",
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" pass "
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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": "code",
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"collapsed": false,
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"input": [
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"print('first 3 rows:')\n",
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"for row in range(3):\n",
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" print(csv_cont[row])"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"first 3 rows:\n",
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"['name', 'column1', 'column2', 'column3']\n",
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"['abc', 1.1, 4.2, 1.2]\n",
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"['def', 2.1, 1.4, 5.2]\n"
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]
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}
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],
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"prompt_number": 9
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},
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{
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"cell_type": "markdown",
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 5
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"prompt_number": 10
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},
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{
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"cell_type": "markdown",
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]
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}
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],
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"prompt_number": 6
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"prompt_number": 11
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},
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"cell_type": "markdown",
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 28
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"prompt_number": 12
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},
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{
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"cell_type": "code",
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 29
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"prompt_number": 13
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},
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"cell_type": "code",
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]
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}
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],
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"prompt_number": 32
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"prompt_number": 14
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},
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{
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"cell_type": "markdown",
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 34
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"prompt_number": 15
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},
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{
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"cell_type": "markdown",
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]
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}
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],
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"prompt_number": 35
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"prompt_number": 16
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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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"language": "python",
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"metadata": {},
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"outputs": []
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}
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],
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"metadata": {}

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