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nice workbook #2

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847822e
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hyosubkim Apr 8, 2020
7bb0cfe
Merge remote-tracking branch 'upstream/master'
hyosubkim Apr 8, 2020
8573086
minor edits to markdown cells
hyosubkim Apr 10, 2020
2e0c6d6
initial commit
hyosubkim Apr 17, 2020
4a4eeff
Merge remote-tracking branch 'upstream/master'
hyosubkim Apr 17, 2020
6ea582e
Merge remote-tracking branch 'upstream/master'
hyosubkim Apr 18, 2020
9bead55
Merge remote-tracking branch 'upstream/master'
hyosubkim Apr 20, 2020
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6 changes: 6 additions & 0 deletions .ipynb_checkpoints/test-checkpoint.ipynb
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Original file line number Diff line number Diff line change
@@ -0,0 +1,6 @@
{
"cells": [],
"metadata": {},
"nbformat": 4,
"nbformat_minor": 4
}
2 changes: 1 addition & 1 deletion .ipynb_checkpoints/w2-checkpoint.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"First, we will go through **numpy** arrays!"
"First, we will go through **numpy** arrays!!"
]
},
{
Expand Down
59 changes: 59 additions & 0 deletions test.ipynb
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@@ -0,0 +1,59 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"6\n"
]
}
],
"source": [
"x = 4 + 2\n",
"print(x)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
223 changes: 21 additions & 202 deletions w3/w2.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"First, we will go through **numpy** arrays!"
"First, we will go through **numpy** arrays!!"
]
},
{
Expand Down Expand Up @@ -65,7 +65,7 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 4,
"metadata": {},
"outputs": [
{
Expand All @@ -74,7 +74,7 @@
"array([3, 2, 3])"
]
},
"execution_count": 8,
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
Expand Down Expand Up @@ -159,7 +159,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"**How to import a csv jupyter**\n",
"**How to import a csv file to a jupyter notebook**\n",
"\n",
"\n",
"Here I am importing a csv file to jupyter. It is important to know how to import these files to python because all our data are going to be written into csv files hereafter. Note that I have imported a library called pandas. It is a python library that\n",
Expand All @@ -168,209 +168,28 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 5,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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" <td>-5.5</td>\n",
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" <td>11.5</td>\n",
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" <tr>\n",
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" <td>-7.5</td>\n",
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" <td>-8.0</td>\n",
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" <td>-3.0</td>\n",
" <td>-12.5</td>\n",
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" <td>4.0</td>\n",
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" <td>2.0</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>-7.5</td>\n",
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" <td>-8.0</td>\n",
" <td>-18.5</td>\n",
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" <td>-13.0</td>\n",
" <td>4.0</td>\n",
" <td>-15.0</td>\n",
" <td>-6.0</td>\n",
" <td>-11.0</td>\n",
" <td>...</td>\n",
" <td>1.5</td>\n",
" <td>10.0</td>\n",
" <td>0.0</td>\n",
" <td>12.5</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>6.0</td>\n",
" <td>2.5</td>\n",
" <td>5.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>-6.0</td>\n",
" <td>-15.5</td>\n",
" <td>-5.5</td>\n",
" <td>-17.5</td>\n",
" <td>0.0</td>\n",
" <td>-13.5</td>\n",
" <td>0.0</td>\n",
" <td>-15.5</td>\n",
" <td>-5.0</td>\n",
" <td>-11.0</td>\n",
" <td>...</td>\n",
" <td>-0.5</td>\n",
" <td>9.5</td>\n",
" <td>0.5</td>\n",
" <td>13.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.5</td>\n",
" <td>6.5</td>\n",
" <td>3.0</td>\n",
" <td>6.5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 30 columns</p>\n",
"</div>"
],
"text/plain": [
" Shape1x Shape1y Shape2x Shape2y Shape3x Shape3y Shape4x Shape4y \\\n",
"0 -6.0 -15.5 -5.5 -13.5 -5.0 -15.0 5.5 -10.5 \n",
"1 -6.0 -17.0 -5.5 -14.5 -5.0 -14.0 6.5 -10.5 \n",
"2 -7.5 -17.5 -8.0 -15.5 -3.0 -12.5 6.5 -14.0 \n",
"3 -7.5 -16.0 -8.0 -18.5 -2.0 -13.0 4.0 -15.0 \n",
"4 -6.0 -15.5 -5.5 -17.5 0.0 -13.5 0.0 -15.5 \n",
"\n",
" Shape5x Shape5y ... Shape11x Shape11y Shape12x Shape12y Shape13x \\\n",
"0 -5.0 -14.0 ... 5.5 8.5 1.5 10.0 -0.5 \n",
"1 -5.5 -13.5 ... 5.0 9.5 1.5 11.0 -0.5 \n",
"2 -6.0 -13.0 ... 4.0 9.5 -0.5 12.0 -0.5 \n",
"3 -6.0 -11.0 ... 1.5 10.0 0.0 12.5 NaN \n",
"4 -5.0 -11.0 ... -0.5 9.5 0.5 13.0 NaN \n",
"\n",
" Shape13y Shape14x Shape14y Shape15x Shape15y \n",
"0 9.5 -3.0 7.0 0.5 6.5 \n",
"1 11.5 -1.0 6.5 1.0 5.5 \n",
"2 13.0 -0.5 6.0 2.0 5.0 \n",
"3 NaN 0.0 6.0 2.5 5.5 \n",
"4 NaN 0.5 6.5 3.0 6.5 \n",
"\n",
"[5 rows x 30 columns]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
"ename": "FileNotFoundError",
"evalue": "[Errno 2] File C:\\Users\\kanee\\Desktop\\KIM LAB\\Coding Sessions\\W2\\sd.csv does not exist: 'C:\\\\Users\\\\kanee\\\\Desktop\\\\KIM LAB\\\\Coding Sessions\\\\W2\\\\sd.csv'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-5-3841656396cd>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mr'C:\\Users\\kanee\\Desktop\\KIM LAB\\Coding Sessions\\W2\\sd.csv'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m#here copy and paste the path where the 'sd.csv'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;31m#file is. Note that I am assigning the name df to the new pandas dataframe. #the path should be between '(path...)'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m#this function just print out the first few rows of the dataframe. I am not sure if there is a way to look up all the\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;31m#rows. Please open the csv file and make sure you know how the data is arranged in the excel file and in the pandas DataFrame.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/anaconda3/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, dialect, error_bad_lines, warn_bad_lines, delim_whitespace, low_memory, memory_map, float_precision)\u001b[0m\n\u001b[1;32m 674\u001b[0m )\n\u001b[1;32m 675\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 676\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 677\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 678\u001b[0m \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/anaconda3/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m 446\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 447\u001b[0m \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 448\u001b[0;31m \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfp_or_buf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 449\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 450\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/anaconda3/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m 878\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"has_index_names\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"has_index_names\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 879\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 880\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 881\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 882\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.__cinit__\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._setup_parser_source\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] File C:\\Users\\kanee\\Desktop\\KIM LAB\\Coding Sessions\\W2\\sd.csv does not exist: 'C:\\\\Users\\\\kanee\\\\Desktop\\\\KIM LAB\\\\Coding Sessions\\\\W2\\\\sd.csv'"
]
}
],
"source": [
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