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jeroendereu/batch_rename_fields_shapefile.ipynb

Created June 2, 2017 08:42
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A quick method to rename the fields of a shapefile. All fields can be renamed in one loop.
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batch_rename_fields_shapefile.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# batch rename the fields of a shapefile\n",
"# all fields can be renamed in one loop (unlike ArcMap, where you have to rename fields one by one)\n",
"# Parameter: the old and new fieldnames need to be stored in a textfile (see below)"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import geopandas as gpd\n",
"import pandas as pd\n",
"import fiona\n",
"import tkinter.filedialog as tkfd\n",
"import tkinter.simpledialog as tksd\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# import shapefile, with the 'to be converted' fieldnames/columnnames\n",
"input_shapefile = tkfd.askopenfilename(title = \"Select input shapefile\", \n",
" initialdir = \"C:/\", \n",
" filetypes = ((\"shapefile\", \"*.shp\"),(\"all files\", \"*.*\")))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"shapefile = gpd.read_file(input_shapefile)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>A</th>\n",
" <th>B</th>\n",
" <th>C</th>\n",
" <th>D</th>\n",
" <th>Id</th>\n",
" <th>K</th>\n",
" <th>L</th>\n",
" <th>M</th>\n",
" <th>N</th>\n",
" <th>Sample</th>\n",
" <th>geometry</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
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" <td>POINT (51733.56446929721 185566.2300957716)</td>\n",
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" <td>0</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>5</td>\n",
" <td>2</td>\n",
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" <td>POINT (78627.49070676332 206613.6506294408)</td>\n",
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" <td>42</td>\n",
" <td>52</td>\n",
" <td>32</td>\n",
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" <td>56</td>\n",
" <td>65</td>\n",
" <td>12</td>\n",
" <td>36</td>\n",
" <td>16</td>\n",
" <td>POINT (97102.44873076177 179719.7243919747)</td>\n",
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" <tr>\n",
" <th>3</th>\n",
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" <td>95</td>\n",
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" <td>22</td>\n",
" <td>POINT (85175.57709501592 174107.0789163296)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>22</td>\n",
" <td>11</td>\n",
" <td>0</td>\n",
" <td>22</td>\n",
" <td>5</td>\n",
" <td>22</td>\n",
" <td>11</td>\n",
" <td>2</td>\n",
" <td>33</td>\n",
" <td>25</td>\n",
" <td>POINT (79329.07139121895 189541.8539743536)</td>\n",
" </tr>\n",
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"</table>\n",
"</div>"
],
"text/plain": [
" A B C D Id K L M N Sample \\\n",
"0 1 12 0 2 1 58 3 6 9 12 \n",
"1 0 2 3 5 2 6 8 1 0 15 \n",
"2 42 52 32 36 3 56 65 12 36 16 \n",
"3 4 58 95 2 4 6 0 2 1 22 \n",
"4 22 11 0 22 5 22 11 2 33 25 \n",
"\n",
" geometry \n",
"0 POINT (51733.56446929721 185566.2300957716) \n",
"1 POINT (78627.49070676332 206613.6506294408) \n",
"2 POINT (97102.44873076177 179719.7243919747) \n",
"3 POINT (85175.57709501592 174107.0789163296) \n",
"4 POINT (79329.07139121895 189541.8539743536) "
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# example shapefile\n",
"shapefile.head()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x9e5ff28>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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SVcAS4FJgLzA2IvZLmgg8LuncTGP9tSJiMbAYis+h9vfr5XbbhD/itgl/VOlhmFkf9fYM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\n/wFzGG7bE2GjDAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xa88f1d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# example shapefile plotted\n",
"shapefile.plot()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Open the file -textfileformat- that includes the old fieldnames and the new fieldnames. The file is structured as follows:\n",
"# no header\n",
"# old_fieldname_1;new_fieldname_1\n",
"# old_fieldname_2;new_fieldname_2\n",
"# ...\n",
"info_file = tkfd.askopenfilename(title = \"Select textfile\", \n",
" initialdir = \"C:/\", \n",
" filetypes = ((\"textfile\", \"*.txt\"),(\"all files\", \"*.*\")))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [],
"source": [
"mapping = pd.read_csv(info_file, \n",
" delimiter=\";\", \n",
" lineterminator=\"\\n\", \n",
" header=None)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" <th>1</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>A</td>\n",
" <td>Apricot</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>B</td>\n",
" <td>Banana</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>C</td>\n",
" <td>Cherry</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>D</td>\n",
" <td>Date</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>E</td>\n",
" <td>Elderberry</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>F</td>\n",
" <td>Fig</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>G</td>\n",
" <td>Grape</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>K</td>\n",
" <td>Kiwi</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>L</td>\n",
" <td>Lemon</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>M</td>\n",
" <td>Mango</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>N</td>\n",
" <td>Nectarine</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0 1\n",
"0 A Apricot\n",
"1 B Banana\n",
"2 C Cherry\n",
"3 D Date\n",
"4 E Elderberry\n",
"5 F Fig\n",
"6 G Grape\n",
"7 K Kiwi\n",
"8 L Lemon\n",
"9 M Mango\n",
"10 N Nectarine"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# example textfile with old and new fieldnames\n",
"# NOTE: there are more fieldnames in the textfile (e.g. F;Fig, G;Grape and K;Kiwi) then there are in the shapefile. \n",
"# Only matching names will be changed. Non-matching names will be skipped.\n",
"mapping"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"mapping.columns = ('from', 'to')"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>from</th>\n",
" <th>to</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>A</td>\n",
" <td>Apricot</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>B</td>\n",
" <td>Banana</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>C</td>\n",
" <td>Cherry</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>D</td>\n",
" <td>Date</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>E</td>\n",
" <td>Elderberry</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" from to\n",
"0 A Apricot\n",
"1 B Banana\n",
"2 C Cherry\n",
"3 D Date\n",
"4 E Elderberry"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# example textfile with column names 'from' and 'to'\n",
"mapping.head()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# create a dictionary which includes with the old_fieldnames as index and the new_fieldname as\n",
"dict_mapping = mapping.set_index('from').to_dict()['to']"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"{'A': 'Apricot',\n",
" 'B': 'Banana',\n",
" 'C': 'Cherry',\n",
" 'D': 'Date',\n",
" 'E': 'Elderberry',\n",
" 'F': 'Fig',\n",
" 'G': 'Grape',\n",
" 'K': 'Kiwi',\n",
" 'L': 'Lemon',\n",
" 'M': 'Mango',\n",
" 'N': 'Nectarine'}"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dict_mapping"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# for loop to replace the old fieldnames by the new fieldnames\n",
"new_names = []\n",
"for name in shapefile.columns:\n",
" if name in dict_mapping.keys():\n",
" new_names.append(dict_mapping[name])\n",
" else:\n",
" new_names.append(name)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# add the new fieldnames as column headers in the shapefile\n",
"shapefile.columns = new_names"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Apricot</th>\n",
" <th>Banana</th>\n",
" <th>Cherry</th>\n",
" <th>Date</th>\n",
" <th>Id</th>\n",
" <th>Kiwi</th>\n",
" <th>Lemon</th>\n",
" <th>Mango</th>\n",
" <th>Nectarine</th>\n",
" <th>Sample</th>\n",
" <th>geometry</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>58</td>\n",
" <td>3</td>\n",
" <td>6</td>\n",
" <td>9</td>\n",
" <td>12</td>\n",
" <td>POINT (51733.56446929721 185566.2300957716)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>5</td>\n",
" <td>2</td>\n",
" <td>6</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>15</td>\n",
" <td>POINT (78627.49070676332 206613.6506294408)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>42</td>\n",
" <td>52</td>\n",
" <td>32</td>\n",
" <td>36</td>\n",
" <td>3</td>\n",
" <td>56</td>\n",
" <td>65</td>\n",
" <td>12</td>\n",
" <td>36</td>\n",
" <td>16</td>\n",
" <td>POINT (97102.44873076177 179719.7243919747)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>58</td>\n",
" <td>95</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" <td>POINT (85175.57709501592 174107.0789163296)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>22</td>\n",
" <td>11</td>\n",
" <td>0</td>\n",
" <td>22</td>\n",
" <td>5</td>\n",
" <td>22</td>\n",
" <td>11</td>\n",
" <td>2</td>\n",
" <td>33</td>\n",
" <td>25</td>\n",
" <td>POINT (79329.07139121895 189541.8539743536)</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Apricot Banana Cherry Date Id Kiwi Lemon Mango Nectarine Sample \\\n",
"0 1 12 0 2 1 58 3 6 9 12 \n",
"1 0 2 3 5 2 6 8 1 0 15 \n",
"2 42 52 32 36 3 56 65 12 36 16 \n",
"3 4 58 95 2 4 6 0 2 1 22 \n",
"4 22 11 0 22 5 22 11 2 33 25 \n",
"\n",
" geometry \n",
"0 POINT (51733.56446929721 185566.2300957716) \n",
"1 POINT (78627.49070676332 206613.6506294408) \n",
"2 POINT (97102.44873076177 179719.7243919747) \n",
"3 POINT (85175.57709501592 174107.0789163296) \n",
"4 POINT (79329.07139121895 189541.8539743536) "
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# example shapefile with new field/column-names\n",
"# NOTE: only the fieldnames included in the textfile have been changed, the other fields (e.g. sample, id) remained untouched and are still in the shapefile.\n",
"shapefile.head()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# define the output location and the output filename.shp\n",
"output_shapefile = tkfd.asksaveasfilename(title = \"Select output location and define output filename.shp -don't forget .shp!-\", \n",
" initialdir = \"C:/\", \n",
" filetypes = ((\"shapefile\", \".shp\"), (\"all types\", \"*.*\")))"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# write the shapefile with the new fieldnames to the newly defined shapefile\n",
"shapefile.to_file(output_shapefile)"
]
}
],
"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": "3.6.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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