1+ {
2+ "nbformat" : 4 ,
3+ "nbformat_minor" : 0 ,
4+ "metadata" : {
5+ "kernelspec" : {
6+ "display_name" : " Python 3"
7+ "language" : " python"
8+ "name" : " python3"
9+ },
10+ "language_info" : {
11+ "codemirror_mode" : {
12+ "name" : " ipython"
13+ "version" : 3
14+ },
15+ "file_extension" : " .py"
16+ "mimetype" : " text/x-python"
17+ "name" : " python"
18+ "nbconvert_exporter" : " python"
19+ "pygments_lexer" : " ipython3"
20+ "version" : " 3.5.5"
21+ },
22+ "colab" : {
23+ "name" : " plantilla_colab.ipynb"
24+ "provenance" : [],
25+ "collapsed_sections" : [],
26+ "toc_visible" : true
27+ }
28+ },
29+ "cells" : [
30+ {
31+ "cell_type" : " markdown"
32+ "metadata" : {
33+ "id" : " puKuhMTDYSOZ"
34+ "colab_type" : " text"
35+ },
36+ "source" : [
37+ " # Clonamos el repositorio para obtener los dataSet"
38+ ]
39+ },
40+ {
41+ "cell_type" : " code"
42+ "metadata" : {
43+ "id" : " Uk7PbIdKYSIz"
44+ "colab_type" : " code"
45+ "colab" : {}
46+ },
47+ "source" : [
48+ " !git clone https://github.com/joanby/python-ml-course.git"
49+ ],
50+ "execution_count" : null ,
51+ "outputs" : []
52+ },
53+ {
54+ "cell_type" : " markdown"
55+ "metadata" : {
56+ "id" : " F9QCxSLWYSCo"
57+ "colab_type" : " text"
58+ },
59+ "source" : [
60+ " # Damos acceso a nuestro Drive"
61+ ]
62+ },
63+ {
64+ "cell_type" : " code"
65+ "metadata" : {
66+ "id" : " JxP0rvkjYR85"
67+ "colab_type" : " code"
68+ "colab" : {}
69+ },
70+ "source" : [
71+ " from google.colab import drive\n "
72+ " drive.mount('/content/drive')"
73+ ],
74+ "execution_count" : null ,
75+ "outputs" : []
76+ },
77+ {
78+ "cell_type" : " markdown"
79+ "metadata" : {
80+ "id" : " jeICtWYtYR3B"
81+ "colab_type" : " text"
82+ },
83+ "source" : [
84+ " # Test it"
85+ ]
86+ },
87+ {
88+ "cell_type" : " code"
89+ "metadata" : {
90+ "id" : " 5cxGKVrnYRxY"
91+ "colab_type" : " code"
92+ "colab" : {}
93+ },
94+ "source" : [
95+ " !ls '/content/drive/My Drive' "
96+ ],
97+ "execution_count" : null ,
98+ "outputs" : []
99+ },
100+ {
101+ "cell_type" : " markdown"
102+ "metadata" : {
103+ "id" : " dbVO03VrYRrU"
104+ "colab_type" : " text"
105+ },
106+ "source" : [
107+ " # Google colab tools"
108+ ]
109+ },
110+ {
111+ "cell_type" : " code"
112+ "metadata" : {
113+ "id" : " mMOsP11eYRls"
114+ "colab_type" : " code"
115+ "colab" : {}
116+ },
117+ "source" : [
118+ " from google.colab import files # Para manejar los archivos y, por ejemplo, exportar a su navegador\n "
119+ " import glob # Para manejar los archivos y, por ejemplo, exportar a su navegador\n "
120+ " from google.colab import drive # Montar tu Google drive"
121+ ],
122+ "execution_count" : null ,
123+ "outputs" : []
124+ },
125+ {
126+ "cell_type" : " markdown"
127+ "metadata" : {
128+ "id" : " H_j7iuX7J1mR"
129+ "colab_type" : " text"
130+ },
131+ "source" : [
132+ " # Python3.8"
133+ ]
134+ },
135+ {
136+ "cell_type" : " code"
137+ "metadata" : {
138+ "id" : " 1tmAE_CtK3nk"
139+ "colab_type" : " code"
140+ "colab" : {}
141+ },
142+ "source" : [
143+ " !python3 --version"
144+ ],
145+ "execution_count" : null ,
146+ "outputs" : []
147+ },
148+ {
149+ "cell_type" : " markdown"
150+ "metadata" : {
151+ "id" : " 3a6f0kFwPMEs"
152+ "colab_type" : " text"
153+ },
154+ "source" : [
155+ " # Colab no permite actualizar la version de python, asi que utilizamos miniconda"
156+ ]
157+ },
158+ {
159+ "cell_type" : " markdown"
160+ "metadata" : {
161+ "id" : " PDo7e5RdPU8z"
162+ "colab_type" : " text"
163+ },
164+ "source" : [
165+ " ### Tener paciencia y esperar 1 minuto"
166+ ]
167+ },
168+ {
169+ "cell_type" : " code"
170+ "metadata" : {
171+ "id" : " v8FTFqwNJ3Qy"
172+ "colab_type" : " code"
173+ "colab" : {}
174+ },
175+ "source" : [
176+ " !wget -O mini.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh > /dev/null 2>&1\n "
177+ " !chmod +x mini.sh\n "
178+ " !bash ./mini.sh -b -f -p /usr/local > /dev/null 2>&1\n "
179+ " !conda install -q -y --prefix /usr/local jupyter > /dev/null 2>&1\n "
180+ " !python -m ipykernel install --name \" py38\" --user > /dev/null 2>&1"
181+ ],
182+ "execution_count" : null ,
183+ "outputs" : []
184+ },
185+ {
186+ "cell_type" : " markdown"
187+ "metadata" : {
188+ "id" : " C-M6G1zuSyEy"
189+ "colab_type" : " text"
190+ },
191+ "source" : [
192+ " ### La celda de abajo, ejecutar cada vez que reinicies el kernel."
193+ ]
194+ },
195+ {
196+ "cell_type" : " code"
197+ "metadata" : {
198+ "id" : " 6XDvEAFFShjJ"
199+ "colab_type" : " code"
200+ "colab" : {}
201+ },
202+ "source" : [
203+ " import sys\n "
204+ " #si usamos append nos coge la libreria de python3.6, ya que el so lee de forma secuencial la lista de librerias\n "
205+ " _ = (sys.path.insert(0,\" /usr/local/lib/python3.8/site-packages\" )) #folder librerias python\n "
206+ " sys.path"
207+ ],
208+ "execution_count" : null ,
209+ "outputs" : []
210+ },
211+ {
212+ "cell_type" : " code"
213+ "metadata" : {
214+ "id" : " aJuxFngCSo_J"
215+ "colab_type" : " code"
216+ "colab" : {}
217+ },
218+ "source" : [
219+ " !conda install numpy scipy matplotlib pandas --yes > /dev/null 2>&1\n "
220+ " !conda install -c conda-forge statsmodels --yes > /dev/null 2>&1\n "
221+ " !conda install --channel conda-forge featuretools --yes > /dev/null 2>&1"
222+ ],
223+ "execution_count" : null ,
224+ "outputs" : []
225+ },
226+ {
227+ "cell_type" : " code"
228+ "metadata" : {
229+ "id" : " MxPWmzZ1J5hh"
230+ "colab_type" : " code"
231+ "colab" : {}
232+ },
233+ "source" : [
234+ " !python3 --version"
235+ ],
236+ "execution_count" : null ,
237+ "outputs" : []
238+ }
239+ ]
240+ }
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