Configuring the new tag for pyPI release
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# file GENERATED by distutils, do NOT edit
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# file GENERATED by distutils, do NOT edit
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README
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setup.cfg
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setup.cfg
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setup.py
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setup.py
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pyFTS/__init__.py
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pyFTS/__init__.py
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@ -11,7 +11,7 @@ def get_data(field):
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def get_dataframe():
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def get_dataframe():
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dat = common.get_dataframe('data/NASDAQ.csv.bz2',
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dat = common.get_dataframe('data/NASDAQ.csv.bz2',
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'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/data/NASDAQ.csv.bz2',
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'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/NASDAQ.csv.bz2',
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sep=";", compression='bz2')
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sep=";", compression='bz2')
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return dat
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return dat
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@ -12,7 +12,7 @@ def get_data():
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def get_dataframe():
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def get_dataframe():
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dat = common.get_dataframe('data/TAIEX.csv.bz2',
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dat = common.get_dataframe('data/TAIEX.csv.bz2',
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'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/TAIEX.csv.bz2',
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'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/TAIEX.csv.bz2',
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sep=";", compression='bz2')
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sep=",", compression='bz2')
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dat["Date"] = pd.to_datetime(dat["Date"])
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dat["Date"] = pd.to_datetime(dat["Date"])
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return dat
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return dat
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@ -18,9 +18,17 @@
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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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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 1,
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"metadata": {},
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"metadata": {},
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"outputs": [
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/usr/local/lib/python3.6/dist-packages/statsmodels/compat/pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.\n",
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" from pandas.core import datetools\n"
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]
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},
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{
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{
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"name": "stdout",
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"name": "stdout",
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"output_type": "stream",
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"output_type": "stream",
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@ -58,13 +66,29 @@
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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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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 4,
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"/home/petronio/dados/Dropbox/Doutorado/Codigos/pyFTSsource/pyFTS/notebooks/teste\n"
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]
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}
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],
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"source": [
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"source": [
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"from pyFTS.data import Enrollments\n",
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"#from pyFTS.data import Enrollments\n",
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"\n",
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"\n",
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"enrollments = Enrollments.get_data()"
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"#enrollments = Enrollments.get_data()\n",
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"\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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"import os\n",
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"import pkg_resources\n",
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"from pathlib import Path\n",
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"from urllib import request\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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{
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{
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32
setup.py
32
setup.py
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from distutils.core import setup
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from distutils.core import setup
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from distutils.command.install import install as _install
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class install(_install):
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def run(self):
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_install.run(self)
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from pyFTS.data import INMET,Enrollments,AirPassengers,NASDAQ,SONDA,SP500,sunspots,TAIEX
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print("Downloading data assets:")
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print("TAIEX")
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TAIEX.get_data()
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print("sunspots")
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sunspots.get_data()
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print("SP500")
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SP500.get_dataframe()
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print("SONDA")
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SONDA.get_dataframe()
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print("NASDAQ")
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NASDAQ.get_dataframe()
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print("AirPassengers")
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AirPassengers.get_data()
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print("Enrollments")
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Enrollments.get_data()
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print("INMET")
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INMET.get_dataframe()
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setup(
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setup(
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name='pyFTS',
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name='pyFTS',
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@ -9,7 +35,7 @@ setup(
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#package_data={'pyFTS.data': ['*.csv','*.csv.bz2']},
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#package_data={'pyFTS.data': ['*.csv','*.csv.bz2']},
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#data_files=[('data', ['pyFTS/data/Enrollments.csv', 'pyFTS/data/AirPassengers.csv'])],
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#data_files=[('data', ['pyFTS/data/Enrollments.csv', 'pyFTS/data/AirPassengers.csv'])],
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#include_package_data=True,
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#include_package_data=True,
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version='1.2.3',
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version='1.2.0',
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description='Fuzzy Time Series for Python',
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description='Fuzzy Time Series for Python',
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author='Petronio Candido L. e Silva',
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author='Petronio Candido L. e Silva',
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author_email='petronio.candido@gmail.com',
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author_email='petronio.candido@gmail.com',
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'Programming Language :: Python :: 3.5',
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'Programming Language :: Python :: 3.5',
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'Programming Language :: Python :: 3.6',
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'Programming Language :: Python :: 3.6',
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],
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],
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#install_requires=[
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cmdclass={'install': install},
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# 'numpy','pandas','matplotlib','dill','copy','dispy','multiprocessing','joblib','statsmodels'
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#]
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)
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)
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