repo_name stringlengths 6 112 | path stringlengths 4 204 | copies stringlengths 1 3 | size stringlengths 4 6 | content stringlengths 714 891k | license stringclasses 15
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class |
|---|---|---|---|---|---|---|---|---|---|---|
adamrvfisher/TechnicalAnalysisLibrary | PriceRelativeRemoteSignalATROptimizerTwoAsset.py | 1 | 7759 | # -*- coding: utf-8 -*-
"""
Created on Wed Aug 30 19:07:37 2017
@author: AmatVictoriaCuramIII
"""
import numpy as np
import random as rand
import pandas as pd
import time as t
from DatabaseGrabber import DatabaseGrabber
from YahooGrabber import YahooGrabber
Empty = []
Dataset = pd.DataFrame()
Portfolio =... | apache-2.0 | -6,308,838,753,224,976,000 | 36.61194 | 101 | 0.608197 | false |
neutrons/FastGR | addie/processing/idl/table_handler.py | 1 | 22403 | from __future__ import (absolute_import, division, print_function)
#import re
import glob
import os
import numpy as np
from qtpy.QtCore import (Qt)
from qtpy.QtGui import (QCursor)
from qtpy.QtWidgets import (QFileDialog, QMenu, QMessageBox, QTableWidgetSelectionRange)
import addie.processing.idl.populate_master_table... | mit | 796,581,622,623,209,200 | 39.148746 | 120 | 0.573138 | false |
ryanjmccall/nupic.research | union_pooling/union_pooling/experiments/union_sdr_overlap/plot_experiment.py | 4 | 4392 | #!/usr/bin/env python
# ----------------------------------------------------------------------
# Numenta Platform for Intelligent Computing (NuPIC)
# Copyright (C) 2015, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions ... | gpl-3.0 | -4,415,004,528,747,624,400 | 30.826087 | 77 | 0.673042 | false |
AhmedHani/Kaggle-Machine-Learning-Competitions | Medium/Toxic Comment Classification Challenge/train_ffnn.py | 1 | 1063 | import numpy as np
import pandas as pd
from keras.models import Model
from keras.layers import Dense, Embedding, Input
from keras.layers import LSTM, Bidirectional, GlobalMaxPool1D, Dropout
from keras.preprocessing import text, sequence
from keras.callbacks import EarlyStopping, ModelCheckpoint
max_features = 20000
m... | mit | 61,240,177,327,376,260 | 35.689655 | 88 | 0.775165 | false |
ecervera/mindstorms-nb | nxt/functions.py | 1 | 7333 | import json
import shutil
from IPython.core.display import display, HTML
def configure(n):
config = {
'version' : 'nxt',
'number' : n
}
with open('../task/robot_config.json', 'w') as f:
json.dump(config, f)
shutil.copyfile('./functions.py', '../task/functions.py')
print("\x... | mit | -1,915,779,626,699,435,000 | 34.634146 | 346 | 0.609309 | false |
leojohnthomas/ahkab | ekv.py | 1 | 25762 | # -*- coding: iso-8859-1 -*-
# ekv.py
# Partial implementation of the EKV 3.0 MOS transistor model
# Copyright 2010 Giuseppe Venturini
#
# The EKV model was developed by Matthias Bucher, Christophe Lallement,
# Christian Enz, Fabien Théodoloz, François Krummenacher at the Electronics
# Laboratories, Swiss Federal In... | gpl-2.0 | 2,957,746,477,690,178,000 | 33.296937 | 251 | 0.636914 | false |
ceroytres/RBM | binary_RBM.py | 1 | 4503 | from __future__ import print_function
import numpy as np
from numba import jit
class binary_RBM(object):
def __init__(self,n_visible=None,n_hidden=256,batchSize=256,lr=0.1,alpha=0,
mu=.95,epochs=1,k=10):
self.n_hidden=n_hidden
self.n_visible=n_visible
self.batchSize=batch... | mit | -6,674,141,656,296,916,000 | 28.431373 | 90 | 0.487897 | false |
bloyl/mne-python | mne/channels/tests/test_layout.py | 4 | 14417 | # Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Denis Engemann <denis.engemann@gmail.com>
# Martin Luessi <mluessi@nmr.mgh.harvard.edu>
# Eric Larson <larson.eric.d@gmail.com>
#
# License: Simplified BSD
import copy
import os.path as op
import numpy as np
from numpy.testing im... | bsd-3-clause | -6,684,274,647,835,185,000 | 38.283379 | 79 | 0.623569 | false |
mailund/pairwise-IM | IMSystem.py | 1 | 3547 | from numpy import matrix
from scipy.linalg import expm
## Constants used as indices in rate and transition matrices
LINEAGES_IN_SEP_POPS = 0
LINEAGES_IN_POP_1 = 1
LINEAGES_IN_POP_2 = 2
COALESCED = 3
NOT_COALESCED = [0,1,2]
def make_rate_matrix(c1, c2, m12, m21):
'''Create a rate matrix based on coalescence rates ... | gpl-3.0 | 5,477,560,428,867,526,000 | 36.336842 | 95 | 0.572597 | false |
ky822/Data_Bootcamp | Code/Python/WB_wdi_all.py | 2 | 2294 | """
Messing around with World Bank data. We start by reading in the whole WDI
from the online csv. Since the online file is part of a zipped collection,
this turned into an exploration of how to handle zip files -- see Section 1.
Section 2 (coming) does slicing and plotting.
Prepared for the NYU Course "Data Boo... | mit | 3,442,475,768,866,982,000 | 30.424658 | 102 | 0.709677 | false |
AtsushiSakai/jsk_visualization_packages | jsk_rqt_plugins/src/jsk_rqt_plugins/hist.py | 1 | 7882 | #!/usr/bin/env python
from rqt_gui_py.plugin import Plugin
from python_qt_binding import loadUi
from python_qt_binding.QtCore import Qt, QTimer, qWarning, Slot
from python_qt_binding.QtGui import QAction, QIcon, QMenu, QWidget
from python_qt_binding.QtGui import QWidget, QVBoxLayout, QSizePolicy, QColor
from rqt_py_com... | mit | 4,489,442,462,833,596,400 | 39.214286 | 113 | 0.632581 | false |
guziy/basemap | examples/save_background.py | 2 | 1364 | from __future__ import (absolute_import, division, print_function)
import matplotlib, sys
matplotlib.use('Agg')
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
# this example shows how to save a map background and
# reuse it in another figure.
# make sure we have all the same properties on a... | gpl-2.0 | 4,759,339,645,438,496,000 | 32.268293 | 66 | 0.76173 | false |
vatsan/pandas_via_psql | setup.py | 2 | 4301 | from setuptools import setup, find_packages
from distutils.util import convert_path
import os,sys
from fnmatch import fnmatchcase
# Provided as an attribute, so you can append to these instead
# of replicating them:
standard_exclude = ('*.pyc', '*$py.class', '*~', '.*', '*.bak')
standard_exclude_directories = ('.*', '... | bsd-2-clause | -4,267,674,333,726,588,400 | 40.355769 | 95 | 0.549872 | false |
stephane-caron/pymanoid | examples/contact_stability/zmp_support_area.py | 3 | 5631 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (C) 2015-2020 Stephane Caron <stephane.caron@normalesup.org>
#
# This file is part of pymanoid <https://github.com/stephane-caron/pymanoid>.
#
# pymanoid is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public Lic... | gpl-3.0 | -3,208,270,963,893,853,000 | 30.110497 | 79 | 0.640206 | false |
rema-git/lichtmalen | image_to_tpm2.py | 1 | 3589 | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
Created on Mon Oct 27 00:33:17 2014
@author: Reinhardt A.W. Maier <rema@zaehlwerk.net>
"""
import os
import argparse
import binascii
import numpy as np
import Image as pil
#import textwrap
#import matplotlib.pyplot as plt
def tpm2(image, lastFrameBlack=False):
"""
... | gpl-3.0 | -8,740,749,091,339,044,000 | 28.178862 | 111 | 0.629145 | false |
activitynet/ActivityNet | Evaluation/get_ava_active_speaker_performance.py | 1 | 8421 | r"""Compute active speaker detection performance for the AVA dataset.
Please send any questions about this code to the Google Group ava-dataset-users:
https://groups.google.com/forum/#!forum/ava-dataset-users
Example usage:
python -O get_ava_active_speaker_performance.py \
-g testdata/eval.csv \
-p testdata/predictio... | mit | -3,192,975,491,083,719,000 | 33.093117 | 80 | 0.676879 | false |
CCS-Lab/hBayesDM | Python/hbayesdm/models/_pst_Q.py | 1 | 10143 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import Inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import pst_preprocess_func
__all__ = ['pst_Q']
class PstQ(TaskModel):
def __init__(self, **kwargs):
super().__ini... | gpl-3.0 | -2,116,428,267,287,271,000 | 42.161702 | 566 | 0.643104 | false |
linebp/pandas | pandas/tests/dtypes/test_inference.py | 1 | 35947 | # -*- coding: utf-8 -*-
"""
These the test the public routines exposed in types/common.py
related to inference and not otherwise tested in types/test_common.py
"""
from warnings import catch_warnings
import collections
import re
from datetime import datetime, date, timedelta, time
from decimal import Decimal
import n... | bsd-3-clause | 3,442,768,526,486,067,000 | 33.300573 | 79 | 0.567919 | false |
Ernestyj/PyStudy | finance/DaysTest/MICAnalysis.py | 1 | 4363 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
from minepy import MINE
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="white", context="talk")
from sklearn import preprocessing
pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 30)
p... | apache-2.0 | -3,788,239,183,814,603,000 | 29.06993 | 104 | 0.604327 | false |
LouisPlisso/analysis_tools | complements.py | 1 | 51874 | #!/usr/bin/env python
"""Module to provide missing stats for streaming analysis
"""
from __future__ import division, print_function
from operator import concat, itemgetter
from collections import defaultdict
from itertools import islice, cycle
from random import random
from tempfile import NamedTemporaryFile
import os... | gpl-3.0 | 7,636,610,822,924,463,000 | 48.640191 | 81 | 0.471758 | false |
elsehow/moneybot | moneybot/fund.py | 1 | 6641 | # -*- coding: utf-8 -*-
from datetime import datetime
from logging import getLogger
from time import sleep
from time import time
from typing import Generator
from copy import deepcopy
import pandas as pd
from pyloniex.errors import PoloniexServerError
from moneybot.market.adapters import MarketAdapter
from moneybot.s... | bsd-3-clause | -663,076,200,772,912,300 | 38.064706 | 94 | 0.596597 | false |
jdhp-sap/sap-cta-data-pipeline | utils/simtel_to_fits_nectarcam.py | 2 | 15361 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright (c) 2017 Jérémie DECOCK (http://www.jdhp.org)
# This script is provided under the terms and conditions of the MIT license:
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (th... | mit | 4,052,761,697,814,277,600 | 43.909357 | 177 | 0.528094 | false |
X-DataInitiative/tick | examples/plot_prox_example.py | 2 | 1432 | """
==============================
Examples of proximal operators
==============================
Plot examples of proximal operators available in tick
"""
import numpy as np
import matplotlib.pyplot as plt
from tick.prox import ProxL1, ProxElasticNet, ProxL2Sq, \
ProxPositive, ProxSlope, ProxTV, ProxZero, ProxBina... | bsd-3-clause | 2,166,794,253,541,222,400 | 28.833333 | 76 | 0.617318 | false |
byuflowlab/vawt-wake-model | wake_model/validation/tescione_val.py | 2 | 34805 | import numpy as np
import matplotlib.pyplot as plt
import csv
from VAWT_Wake_Model import velocity_field
from scipy.io import loadmat
from numpy import fabs
from os import path
from matplotlib import rcParams
rcParams['font.family'] = 'Times New Roman'
rom = True
# rom = False
r = 0.5 # radius
v = 1.0 # velocity
v... | mit | 3,470,095,439,570,599,400 | 42.724874 | 696 | 0.594139 | false |
hchim/stockanalyzer | analysis/indicators.py | 1 | 13443 | import pandas as pd
import numpy as np
from analysis.basic import compute_daily_returns
import math
def sma(prices, params):
"""
Calculate the simple moving average indicator.
Parameters
----------
prices: DataFrame
params: dict
e.g. {"windows": [5, 10]}
Returns
---------... | mit | 4,074,898,968,506,970,000 | 26.050302 | 97 | 0.583054 | false |
CVerhoosel/nutils | examples/burgers.py | 1 | 3390 | #! /usr/bin/python3
#
# In this script we solve the Burgers equation on a 1D or 2D periodic dommain,
# starting from a centered Gaussian and convecting in the positive direction of
# the first coordinate.
import nutils, numpy
# The main function defines the parameter space for the script. Configurable
# parameters ar... | mit | 8,277,718,623,519,437,000 | 41.375 | 154 | 0.70708 | false |
burakbayramli/dersblog | vision/vision_02/plot3d.py | 2 | 2141 | from mpl_toolkits.mplot3d import axes3d
from matplotlib.patches import Circle, PathPatch
import matplotlib.pyplot as plt
from matplotlib.transforms import Affine2D
from mpl_toolkits.mplot3d import art3d
import numpy as np
def plot_vector(fig, orig, v, color='blue'):
ax = fig.gca(projection='3d')
orig = np.array(... | gpl-3.0 | 8,619,222,826,841,033,000 | 35.288136 | 89 | 0.632882 | false |
duttashi/Data-Analysis-Visualization | scripts/general/anovaTest.py | 1 | 6339 | # Importing the required libraries
# Note %matplotlib inline works only for ipython notebook. It will not work for PyCharm. It is used to show the plot distributions
#%matplotlib inline
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import statsmodels.formula.api as smf
imp... | mit | 4,783,858,996,819,061,000 | 44.934783 | 132 | 0.762108 | false |
DTMilodowski/LiDAR_canopy | src/PAI_limitations_figures.py | 1 | 22708 | #===============================================================================
# PAI_limitations_figures.py
# D.T.Milodowski, November 2017
#-------------------------------------------------------------------------------
# This function contains the scripts used to produce the figures in the paper:
# "Point density i... | gpl-3.0 | 4,718,651,781,681,082,000 | 39.695341 | 173 | 0.664259 | false |
camallen/aggregation | experimental/chicago/aggregation.py | 2 | 6819 | #!/usr/bin/env python
__author__ = 'greghines'
import numpy as np
import matplotlib.pyplot as plt
import csv
import sys
import os
import pymongo
import matplotlib.cbook as cbook
import random
import bisect
animals = [u'bike', u'grayFox', u'livestock', u'foxSquirrel', u'deer', u'rat', u'mink', u'human', u'beaver', u'mo... | apache-2.0 | 2,238,402,340,212,246,000 | 28.266094 | 363 | 0.63895 | false |
JustinNoel1/ML-Course | bayes/bayesian-regression/python/bayreg.py | 1 | 3784 | #Implementation of Bayesian polynomial regression using pymc3
from pymc3 import *
import numpy as np
import matplotlib.pyplot as plt
from sklearn.preprocessing import PolynomialFeatures
import pandas as pd
import theano
from scipy.stats.kde import gaussian_kde
# set sample size
NUM_SAMPLES = 200
# set desired stand... | apache-2.0 | 3,971,333,095,095,953,400 | 34.698113 | 237 | 0.647199 | false |
karstenw/nodebox-pyobjc | examples/Extended Application/matplotlib/examples/statistics/hist.py | 1 | 3990 | """
==========
Histograms
==========
Demonstrates how to plot histograms with matplotlib.
"""
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import colors
# from matplotlib.ticker import PercentFormatter
# nodebox section
if __name__ == '__builtin__':
# were in nodebox
import os
impor... | mit | 5,362,261,448,032,349,000 | 28.555556 | 82 | 0.607018 | false |
dashmoment/facerecognition | py/apps/scripts/preprocessing_experiments.py | 2 | 5764 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) Philipp Wagner. All rights reserved.
# Licensed under the BSD license. See LICENSE file in the project root for full license information.
import sys, os
sys.path.append("../..")
# facerec
from facerec.feature import Fisherfaces, PCA, SpatialHistogram, Iden... | bsd-3-clause | 7,224,324,888,766,617,000 | 37.172185 | 125 | 0.629077 | false |
wangsix/cluster | bins/xmeans_demo.py | 1 | 2365 | '''
Created on Mar 15, 2012
@author: Wang
'''
import numpy as np
from scipy.cluster.vq import *
import pylab
import matplotlib.pyplot as plt
import cluster
plt.figure()
class1 = np.array(np.random.standard_normal((2,2))) + np.array([5,5])
class2 = np.array(np.random.standard_normal((1,2)))
class3 = np.array(np.ran... | gpl-3.0 | 944,239,356,310,498,200 | 38.433333 | 81 | 0.663002 | false |
zehpunktbarron/iOSMAnalyzer | scripts/c6_landuse.py | 1 | 3381 | # -*- coding: utf-8 -*-
#!/usr/bin/python2.7
#description :This file creates a plot: Calculates the development of all objects with a "landuse"-tag
#author :Christopher Barron @ http://giscience.uni-hd.de/
#date :19.01.2013
#version :0.1
#usage :python pyscript.py
#==========... | gpl-3.0 | 5,170,037,965,798,347,000 | 27.411765 | 131 | 0.677906 | false |
KellyBlack/Precalculus | functions/img/composition.py | 1 | 1856 | #!/usr/bin/python
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.path as path
from matplotlib.patches import FancyArrowPatch
from matplotlib.patches import Ellipse
import math
import sys
from BasicPlot import BasicPlot
plotter = BasicPlot()
plt.figure(num=1,... | gpl-3.0 | -7,112,809,213,044,979,000 | 28.460317 | 66 | 0.637392 | false |
bwvdnbro/HydroCodeSpherical1D | paper_workflows/fig_convergence_seed.py | 1 | 3451 | import numpy as np
import matplotlib
matplotlib.use("Agg")
import pylab as pl
import scipy.special.lambertw as lambertw
import sys
if len(sys.argv) < 2:
print "Usage: python fig_convergence_seed.py amplitude"
exit()
amplitude = float(sys.argv[1])
pl.rcParams["text.usetex"] = True
pl.rcParams["figure.figsize"] = ... | agpl-3.0 | -8,984,461,688,933,214,000 | 26.830645 | 80 | 0.580122 | false |
JiaMingLin/de-identification | test/test_measure_func.py | 1 | 1068 | import common.constant as c
from django.test import TestCase
from common.data_utilities import DataUtils
from utility_measure.measure_func import UserQuery
TEST_DATA_PATH = c.TEST_ORIGIN_DATA_PATH
class TestMeasureFunc(TestCase):
def setUp(self):
self.queries = [
"Age > 50 and workclass == 'Self-emp-not-inc'",
... | apache-2.0 | -6,687,662,837,570,749,000 | 38.592593 | 89 | 0.716292 | false |
yousrabk/mne-python | mne/viz/epochs.py | 2 | 60751 | """Functions to plot epochs data
"""
# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Denis Engemann <denis.engemann@gmail.com>
# Martin Luessi <mluessi@nmr.mgh.harvard.edu>
# Eric Larson <larson.eric.d@gmail.com>
# Jaakko Leppakangas <jaeilepp@student.jyu.f... | bsd-3-clause | -2,441,897,527,907,268,600 | 39.392952 | 79 | 0.544682 | false |
romain-fontugne/disco | src/plotFunctions.py | 1 | 16050 | from __future__ import division
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot as plt
import matplotlib.dates as mdates
#plt=matplotlib.pyplot
import datetime as dt
from datetime import datetime
import numpy as np
import traceback
import os
import pandas as pd
import threading
import operator
fr... | gpl-3.0 | 1,524,251,697,561,568,300 | 34.274725 | 150 | 0.516449 | false |
ericmjl/bokeh | examples/app/movies/main.py | 1 | 4195 | import sqlite3 as sql
from os.path import dirname, join
import numpy as np
import pandas.io.sql as psql
from bokeh.io import curdoc
from bokeh.layouts import column, layout
from bokeh.models import ColumnDataSource, Div, Select, Slider, TextInput
from bokeh.plotting import figure
from bokeh.sampledata.movies_data imp... | bsd-3-clause | 6,006,346,634,513,225,000 | 35.163793 | 121 | 0.65435 | false |
keras-team/keras-io | examples/timeseries/timeseries_weather_forecasting.py | 1 | 11224 | """
Title: Timeseries forecasting for weather prediction
Authors: [Prabhanshu Attri](https://prabhanshu.com/github), [Yashika Sharma](https://github.com/yashika51), [Kristi Takach](https://github.com/ktakattack), [Falak Shah](https://github.com/falaktheoptimist)
Date created: 2020/06/23
Last modified: 2020/07/20
Descri... | apache-2.0 | -1,283,266,379,708,159,700 | 28.382199 | 252 | 0.663845 | false |
rohandavidg/CONCORD-VCF | bin/csv_to_dict.py | 1 | 1860 | #!/dlmp/sandbox/cgslIS/rohan/Python-2.7.11/python
"""
this script converts a csv to dict
"""
import pandas as pd
import numpy as np
import re
import pprint
import warnings
from collections import defaultdict
warnings.filterwarnings("ignore")
def main(csv_file):
vcf_dict, snp_dict, indel_dict = parse_csv(csv_file... | mit | 2,124,828,647,953,762,800 | 34.09434 | 136 | 0.610215 | false |
meisamhe/GPLshared | Research_Projects_UTD/Tensorflow_tutorial/tensor_flow.py | 1 | 1071 | gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.333)
sess = tf.InteractiveSession(gpu_options=gpu_options)
import tensorflow as tf
import numpy as np
import edward as ed
import numpy as np
import tensorflow as tf
from edward.models import Normal
from edward.util import rbf
from edward.models import ... | gpl-3.0 | -8,821,327,175,027,198,000 | 22.282609 | 66 | 0.712418 | false |
wilseypa/warped2-models | scripts/plotChains.py | 1 | 12067 | #!/usr/bin/python
# Calculates statistics and plots the chain metrics from raw data
from __future__ import print_function
import csv
import os, sys
import numpy as np
import scipy as sp
import scipy.stats as sps
import pandas as pd
import re, shutil, tempfile
import itertools, operator
import subprocess
import Gnuplo... | mit | 1,226,787,144,049,247,200 | 35.128743 | 108 | 0.555648 | false |
yhat/ggplot | docs/examples.py | 1 | 13564 | from ggplot import *
import uuid
import seaborn as sns
import pandas as pd
import numpy as np
tips = sns.load_dataset('tips')
import sys
p = ggplot(mtcars, aes(x='mpg', y='cyl', color='steelblue')) + geom_point()
p.save("./examples/example-" + str(uuid.uuid4()) + ".png")
p = ggplot(mtcars, aes(x='mpg', y='cyl')) + ge... | bsd-2-clause | -3,096,100,790,687,385,000 | 48.323636 | 240 | 0.605352 | false |
gfyoung/pandas | pandas/util/_test_decorators.py | 1 | 8663 | """
This module provides decorator functions which can be applied to test objects
in order to skip those objects when certain conditions occur. A sample use case
is to detect if the platform is missing ``matplotlib``. If so, any test objects
which require ``matplotlib`` and decorated with ``@td.skip_if_no_mpl`` will be... | bsd-3-clause | -5,316,504,105,834,613,000 | 28.769759 | 88 | 0.663973 | false |
dattalab/d_code | plotting/plottingRoutines.py | 1 | 6205 | import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats
__all__ = ['plot_avg_and_sem', 'plot_array', 'imshow_array', 'plot_avg_and_comps', 'plot_array_xy']
def plot_avg_and_sem(npArray, axis=1):
"""This routine takes a multidimenionsal numpy array and an axis and then
plots the average... | mit | 3,045,821,880,977,947,600 | 34.255682 | 124 | 0.612409 | false |
Svolcano/python_exercise | dianhua/endday_batch/update_9999_to_-1.py | 1 | 2813 | # -*- coding: utf-8 -*-
"""
Created on Wed May 30 11:09:10 2018
@author: huang
"""
import pymongo
import time
import datetime
import json
import sys
import getopt
import pandas as pd
import numpy as np
np.seterr(divide='ignore', invalid='ignore')
sys.path.append('../')
stdout = sys.stdout
reload(sys... | mit | -4,865,315,491,329,630,000 | 29.920455 | 100 | 0.57036 | false |
AminMahpour/Wigman | main.py | 1 | 4824 | #!/usr/bin/env python3
import operator
import pyBigWig
import sys
import matplotlib.pyplot as pp
import numpy as np
from tqdm import tqdm
# added
def parseconfig(conf_file):
config = open(conf_file, mode="r")
bed_line = []
bw_line =[]
pdf_file = ""
for line in config:
line=line.strip("\... | gpl-2.0 | 4,575,110,508,619,404,300 | 28.777778 | 119 | 0.524461 | false |
planetarymike/IDL-Colorbars | IDL_py_test/033_Blue-Red.py | 1 | 5972 | from matplotlib.colors import LinearSegmentedColormap
from numpy import nan, inf
cm_data = [[0., 0., 0.513725],
[0., 0., 0.513725],
[0., 0., 0.529412],
[0., 0., 0.545098],
[0., 0., 0.560784],
[0., 0., 0.576471],
[0., 0., 0.592157],
[0., 0., 0.607843],
[0., 0., 0.623529],
[0., 0., 0.639216],
[0., 0., 0.654902],
[0., 0.,... | gpl-2.0 | 427,885,498,026,020,350 | 20.79562 | 69 | 0.496651 | false |
alexholcombe/spatiotopic-motion | plotHelpers.py | 1 | 12084 | from psychopy import visual, data, logging
from psychopy.misc import fromFile
import itertools
from math import log
from copy import deepcopy
import pandas as pd
from pandas import DataFrame
import pylab, scipy
import numpy as np
from calcUnderOvercorrect import calcOverCorrected
def agrestiCoull95CI(x, nTrials):
... | mit | -7,298,490,796,033,904,000 | 49.35 | 168 | 0.66708 | false |
cchayward/ALMAHerschelDSFG | Code/dnda.py | 1 | 3270 | """
Shane Bussmann
2014 August 20
Plot dN/dA as a function of angular separation from the center of light. dN =
number of objects between radius 1 and radius 2. dA = area between radius 1
and radius 2.
"""
from astropy.table import Table
import matplotlib
import matplotlib.pyplot as plt
from pylab import savefig... | mit | 1,041,237,110,525,958,500 | 27.434783 | 86 | 0.710703 | false |
walkerps/ICGPM | model.py | 1 | 3369 | import pandas as pd
import numpy as np
import re
from nltk import word_tokenize
from nltk.corpus import wordnet
import pickle
def feature_extraction_approach_2(name):
consonants = ['b','c','d','f','g','h','j','k','l','m','n','p','q','r','s','t','v','w','x','y','z']
vowels = ['a','e','i','o','u']
bobua_consonants = ... | apache-2.0 | -1,384,336,063,342,586,000 | 30.495327 | 178 | 0.658356 | false |
FedoraScientific/salome-gui | tools/CurvePlot/src/python/views/XYView.py | 1 | 25807 | import matplotlib.pyplot as plt
import matplotlib.colors as colors
from View import View
from CurveView import CurveView
from utils import Logger, trQ
from PlotWidget import PlotWidget
from PlotSettings import PlotSettings
from pyqtside import QtGui, QtCore
from pyqtside.QtCore import QObject
from matplotlib.figure im... | lgpl-2.1 | 6,267,137,297,581,451,000 | 35.762108 | 122 | 0.648119 | false |
mohanprasath/Course-Work | data_analysis/uh_data_analysis_with_python/hy-data-analysis-with-python-spring-2020/part04-e16_split_date/test/test_split_date.py | 1 | 2526 | #!/usr/bin/env python3
import unittest
from unittest.mock import patch
import numpy as np
import pandas as pd
from tmc import points
from tmc.utils import load, get_out, patch_helper
module_name="src.split_date"
split_date = load(module_name, "split_date")
main = load(module_name, "main")
ph = patch_helper(module_n... | gpl-3.0 | -8,878,842,569,421,881,000 | 37.861538 | 110 | 0.583531 | false |
priyesh16/thesis | scratch/runall.py | 1 | 3159 | #!/usr/bin/python
import sys
import os
import getopt
import subprocess
from subprocess import call
import re
import numpy as np
import matplotlib.pyplot as plt
from operator import itemgetter
nodelist = []
dijhops = []
airhops = []
files = []
#comblist = []
def sortlist(comblist):
comblist = sorted(comblist,key... | gpl-2.0 | 3,099,603,084,124,216,000 | 23.679688 | 96 | 0.60114 | false |
VicenteYanez/GFA | gfa/field_analysis/fun_fig.py | 1 | 5557 | #! /usr/bin/env python3
"Function to plot the examples script"
import pdb
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import griddata
def greater_absolute(value1, value2):
if abs(value1) >= abs(value2):
return np.array([-value1, value1])
else... | gpl-3.0 | 6,889,460,577,200,876,000 | 26.102439 | 70 | 0.566955 | false |
sahilTakiar/spark | python/pyspark/sql/tests.py | 1 | 276859 | # -*- encoding: utf-8 -*-
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the ... | apache-2.0 | -8,004,263,089,135,259,000 | 41.616225 | 100 | 0.578001 | false |
ChenglongChen/Kaggle_HomeDepot | Code/Igor&Kostia/text_processing.py | 1 | 63488 | # -*- coding: utf-8 -*-
"""
Initial text preprocessing.
Although text processing can be technically done within feature generation functions,
we found it to be very efficient to make all preprocessing first and only then move to
feature generation. It is because the same processed text is used as an input to
generate... | mit | -6,932,427,172,720,892,000 | 49.267617 | 266 | 0.608824 | false |
vsjha18/finplots | rsi.py | 1 | 5108 | """
This module plots Relative Strength Index on a given
axis of matplotlib. All the style attributes are passed
through argument so that it can be independently used
as general purpose library in most of the trivial situations.
However for ease of use we have one more sugar api which needs
onl... | gpl-3.0 | -3,049,561,174,342,176,300 | 33.986301 | 73 | 0.599452 | false |
lthurlow/Network-Grapher | proj/external/matplotlib-1.2.1/doc/mpl_examples/event_handling/poly_editor.py | 3 | 5397 | """
This is an example to show how to build cross-GUI applications using
matplotlib event handling to interact with objects on the canvas
"""
import numpy as np
from matplotlib.lines import Line2D
from matplotlib.artist import Artist
from matplotlib.mlab import dist_point_to_segment
class PolygonInteractor:
"""
... | mit | 106,231,732,139,781,250 | 31.512048 | 117 | 0.593107 | false |
acbecker/BART | samplers.py | 1 | 24227 | """
This file contains the class definition for the sampler MCMCSample classes.
"""
__author__ = 'Brandon C. Kelly'
import numpy as np
import progressbar
from matplotlib import pyplot as plt
import acor
class MCMCSample(object):
"""
Class object for parameter samples generated by a yamcmc++ sampler. This cl... | mit | -7,085,109,834,660,766,000 | 42.339893 | 120 | 0.599909 | false |
Ziqi-Li/bknqgis | pandas/pandas/conftest.py | 7 | 2021 | import pytest
import numpy
import pandas
import pandas.util.testing as tm
def pytest_addoption(parser):
parser.addoption("--skip-slow", action="store_true",
help="skip slow tests")
parser.addoption("--skip-network", action="store_true",
help="skip network tests")
... | gpl-2.0 | -5,245,325,280,974,097,000 | 29.164179 | 78 | 0.6571 | false |
jcchin/MagnePlane | src/hyperloop/Python/mission/tests/test_straight_track.py | 3 | 6317 | from __future__ import division, print_function, absolute_import
import unittest
import numpy as np
try:
from openmdao.api import pyOptSparseDriver
except:
pyOptSparseDriver = None
from openmdao.api import ScipyOptimizer
from pointer.components import Problem, Trajectory, CollocationPhase
from hyperloop.Py... | apache-2.0 | 2,626,302,035,135,182,000 | 42.267123 | 79 | 0.523983 | false |
hdoria/HnTool | HnTool/output/html.py | 1 | 8712 | # -*- coding: utf-8 -*-
#
# HnTool - output module - html
# Copyright (C) 2009-2010 Authors
# Authors:
# * Hugo Doria <mail at hugodoria dot org>
# * Aurelio A. Heckert <aurium at gmail dot com>
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Publ... | gpl-2.0 | -7,514,285,492,901,710,000 | 34.851852 | 143 | 0.473485 | false |
alorenzo175/pvlib-python | pvlib/forecast.py | 1 | 37917 | '''
The 'forecast' module contains class definitions for
retreiving forecasted data from UNIDATA Thredd servers.
'''
import datetime
from netCDF4 import num2date
import numpy as np
import pandas as pd
from requests.exceptions import HTTPError
from xml.etree.ElementTree import ParseError
from pvlib.location import Loca... | bsd-3-clause | 9,113,747,094,163,487,000 | 31.602752 | 79 | 0.57341 | false |
MorganR/gaussian-processes | main.py | 1 | 2611 | # Main test file
import numpy as np
import matplotlib.pyplot as plt
from model_tester import ModelTester, import_model_tester
from data_holder import DataHolder, get_mnist_data
from svgp_tester import SvgpTester
from vgp_tester import VgpTester
from mcmc_tester import McmcTester
num_per_digits = [0]
num_inducing_input... | mit | -2,337,207,912,695,031,300 | 34.780822 | 89 | 0.613558 | false |
cggh/scikit-allel | allel/stats/diversity.py | 1 | 38740 | # -*- coding: utf-8 -*-
import logging
import numpy as np
from allel.model.ndarray import SortedIndex, AlleleCountsArray
from allel.model.util import locate_fixed_differences
from allel.util import asarray_ndim, ignore_invalid, check_dim0_aligned, \
ensure_dim1_aligned, mask_inaccessible
from allel.stats.window... | mit | 9,152,583,474,148,451,000 | 33.374445 | 97 | 0.549535 | false |
cosmir/dev-set-builder | audioset/util.py | 1 | 2590 | from joblib import Parallel, delayed
import numpy as np
import os
import pandas as pd
import tensorflow as tf
from audioset import AUDIO_EMBEDDING_FEATURE_NAME, LABELS
from audioset import START_TIME, TIME, VIDEO_ID
def filebase(fname):
return os.path.splitext(os.path.basename(fname))[0]
def safe_makedirs(dpat... | mit | 4,450,234,088,858,610,700 | 30.975309 | 79 | 0.657529 | false |
kubeflow/pipelines | components/PyTorch/pytorch-kfp-components/pytorch_kfp_components/components/visualization/executor.py | 1 | 9980 | #!/usr/bin/env/python3
#
# Copyright (c) Facebook, Inc. and its affiliates.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required... | apache-2.0 | 7,535,007,747,309,917,000 | 33.895105 | 79 | 0.594088 | false |
OpenPIV/openpiv-python | openpiv/windef.py | 2 | 32332 | # -*- coding: utf-8 -*-
"""
Created on Fri Oct 4 14:04:04 2019
@author: Theo
@modified: Alex, Erich
"""
import os
import numpy as np
import scipy.ndimage as scn
from scipy.interpolate import RectBivariateSpline
import matplotlib.pyplot as plt
from openpiv.tools import imread, Multiprocesser, display_vector_field, ... | gpl-3.0 | 5,857,745,627,380,246,000 | 33.17759 | 79 | 0.592973 | false |
gfyoung/pandas | pandas/core/strings/base.py | 2 | 4702 | import abc
from typing import Pattern, Union
import numpy as np
from pandas._typing import Scalar
class BaseStringArrayMethods(abc.ABC):
"""
Base class for extension arrays implementing string methods.
This is where our ExtensionArrays can override the implementation of
Series.str.<method>. We don'... | bsd-3-clause | -1,347,311,179,181,504,800 | 19.897778 | 81 | 0.595917 | false |
openbermuda/karmapi | karmapi/sunny.py | 1 | 1858 | from karmapi import pigfarm
import curio
import random
from pathlib import Path
class Sunspot(pigfarm.MagicCarpet):
def compute_data(self):
pass
def plot(self):
jup = 11.86
nep = 164.8
sat = 29.4571
x = (1/jup - 1/sat)
jupsat = 1/(2 * x)
x = (1... | gpl-3.0 | -1,704,182,033,431,231,000 | 19.876404 | 105 | 0.492465 | false |
schae234/Camoco | camoco/__init__.py | 1 | 1676 | """
Camoco Library - CoAnalysis of Molecular Components
CacheMoneyCorn
"""
__license__ = """
The "MIT" License
Copyright (c) 2017-2019 Robert Schaefer
Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the ... | mit | -8,831,807,908,612,434,000 | 26.032258 | 79 | 0.78043 | false |
NicWayand/xray | xarray/test/test_dataset.py | 1 | 113381 | # -*- coding: utf-8 -*-
from copy import copy, deepcopy
from textwrap import dedent
try:
import cPickle as pickle
except ImportError:
import pickle
try:
import dask.array as da
except ImportError:
pass
import numpy as np
import pandas as pd
import pytest
from xarray import (align, broadcast, concat, m... | apache-2.0 | 8,000,172,576,457,245,000 | 40.165214 | 165 | 0.537413 | false |
rynecarbone/power_ranker | power_ranker/web/power_plot.py | 1 | 5155 | #!/usr/bin/env python
"""Create box-plot of power rankings vs points scored"""
import logging
from pathlib import Path
import pandas as pd
from plotnine import *
import warnings
__author__ = 'Ryne Carbone'
logger = logging.getLogger(__name__)
def get_team_scores(df_schedule, team, week):
"""Get all scores for a... | mit | -1,320,269,196,353,959,400 | 36.904412 | 111 | 0.634724 | false |
dbarbier/ot-svn | python/doc/sphinxext/numpydoc/plot_directive.py | 3 | 20539 | """
A special directive for generating a matplotlib plot.
.. warning::
This is a hacked version of plot_directive.py from Matplotlib.
It's very much subject to change!
Usage
-----
Can be used like this::
.. plot:: examples/example.py
.. plot::
import matplotlib.pyplot as plt
plt.plot... | gpl-3.0 | -3,953,456,890,394,788,400 | 29.932229 | 83 | 0.534544 | false |
boland1992/seissuite_iran | seissuite/sort_later/pointshape.py | 2 | 2014 | # -*- coding: utf-8 -*-
"""
Created on Mon Jun 20 12:28:32 2015
@author: boland
"""
import sys
sys.path.append("/home/boland/Anaconda/lib/python2.7/site-packages")
import fiona
import shapefile
from shapely import geometry
import numpy as np
import matplotlib.pyplot as plt
import pyproj
import datetime
from matplotli... | gpl-3.0 | -5,387,212,902,189,082,000 | 25.5 | 112 | 0.638034 | false |
damonge/CoLoRe | examples/simple/read_skewers.py | 1 | 1672 | import numpy as np
from astropy.io import fits
import matplotlib.pyplot as plt
hdulist = fits.open('out_srcs_s1_0.fits')
# First HDU contains the source catalog
print(hdulist[1].header.keys)
plt.figure()
plt.hist(hdulist[1].data['Z_COSMO'], bins=100)
print(" ")
# Second HDU contains the density skewers as a FITS ima... | gpl-3.0 | -3,835,317,680,419,938,300 | 33.122449 | 78 | 0.675837 | false |
Procrat/som | som/basic_som.py | 1 | 8023 | #!/usr/bin/env python
# encoding: utf-8
"""A regular SOM."""
from collections import UserList
from .som import normalize
from .som import SOM, Topology, Node
from itertools import chain, islice
from random import choice
from math import exp
import numpy as np
import matplotlib.pyplot as plt
class BasicSOM(SOM):
... | mit | 1,099,930,361,131,690,900 | 37.204762 | 80 | 0.589056 | false |
Ecam-Eurobot-2017/main | code/raspberrypi/graphmap/graphmap.py | 1 | 16765 | import math
import os.path
import operator
import pprint
import networkx as nx
from .utils import GraphUtils
class GraphMap:
CACHE_PATH = 'graphmap.data'
def __init__(self, nodes, triangles, cache=True):
"""
nodes represent the (x, y) address of nodes in the graph.
triangles give the ... | mit | 3,210,404,997,343,590,000 | 40.395062 | 113 | 0.53224 | false |
Kitware/minerva | gaia_tasks/inputs.py | 1 | 7301 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
###############################################################################
# Copyright Kitware Inc. and Epidemico Inc.
#
# Licensed under the Apache License, Version 2.0 ( the "License" );
# you may not use this file except in compliance with the License.
# You ma... | apache-2.0 | 1,753,931,356,030,654,700 | 36.634021 | 98 | 0.567457 | false |
FEniCS/dolfin | test/unit/python/mesh/test_mesh_quality.py | 1 | 3815 | #!/usr/bin/env py.test
"Unit tests for the MeshQuality class"
# Copyright (C) 2013 Garth N. Wells
#
# This file is part of DOLFIN.
#
# DOLFIN is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either ver... | lgpl-3.0 | -8,000,715,879,390,831,000 | 29.52 | 77 | 0.675491 | false |
bellwethers-in-se/defects | src/tca_vs_seer.py | 1 | 1139 | """
Compares TCA with Bellwether Method (SEER to be added)
"""
from __future__ import print_function, division
import os
import sys
root = os.path.join(os.getcwd().split('src')[0], 'src')
if root not in sys.path:
sys.path.append(root)
from SEER.SEER import seer_jur
from TCA.execute import tca_jur
import multipro... | mit | -1,644,647,821,626,126,300 | 26.780488 | 93 | 0.656716 | false |
suriyan/ethnicolr | ethnicolr/census_ln.py | 1 | 3561 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
import argparse
import pandas as pd
from pkg_resources import resource_filename
from .utils import column_exists, fixup_columns
CENSUS2000 = resource_filename(__name__, "data/census/census_2000.csv")
CENSUS2010 = resource_filename(__name__, "data/census/censu... | mit | -221,643,584,409,173,700 | 30.794643 | 78 | 0.564448 | false |
madphysicist/numpy | numpy/fft/_pocketfft.py | 2 | 52860 | """
Discrete Fourier Transforms
Routines in this module:
fft(a, n=None, axis=-1, norm="backward")
ifft(a, n=None, axis=-1, norm="backward")
rfft(a, n=None, axis=-1, norm="backward")
irfft(a, n=None, axis=-1, norm="backward")
hfft(a, n=None, axis=-1, norm="backward")
ihfft(a, n=None, axis=-1, norm="backward")
fftn(a, ... | bsd-3-clause | 2,631,187,690,599,615,000 | 36.172996 | 90 | 0.611313 | false |
aenon/company_10k_analysis | src/company_10k_classifier.py | 1 | 9700 | # -*- coding: utf-8 -*-
"""
Created on Mon Mar 07 22:45:13 2016
@author: Team 6
10-K Classifier
"""
#Importing required modules
import os
import re
import pandas as pd
import numpy as np
from nltk.corpus import stopwords
from sklearn.cross_validation import train_test_split
from sklearn.feature_extractio... | bsd-2-clause | 3,822,367,098,476,669,000 | 37.917695 | 124 | 0.719897 | false |
JakeColtman/bartpy | tests/test_proposer.py | 1 | 2445 | import unittest
from bartpy.data import make_bartpy_data
from bartpy.samplers.unconstrainedtree.proposer import uniformly_sample_grow_mutation, uniformly_sample_prune_mutation
from bartpy.split import Split
from bartpy.tree import LeafNode, Tree, DecisionNode
import pandas as pd
import numpy as np
class TestPruneTr... | mit | -8,221,925,809,584,134,000 | 40.440678 | 125 | 0.693252 | false |
edux300/research | script_create_inbreast_dataset.py | 1 | 6409 | # -*- coding: utf-8 -*-
"""
Created on Wed Aug 2 14:16:54 2017
@author: eduardo
"""
import read_inbreast as readin
import os
from matplotlib import pyplot as plt
import numpy as np
import time
import sys
import pickle
patch_size = 76
safe_padding = 40
inv_resize_factor = 12
resize_factor = float(1/inv_resize_fact... | apache-2.0 | -8,263,579,726,650,916,000 | 30.571429 | 141 | 0.565455 | false |
cggh/scikit-allel | allel/stats/ld.py | 1 | 9253 | # -*- coding: utf-8 -*-
import numpy as np
from allel.stats.window import windowed_statistic
from allel.util import asarray_ndim, ensure_square
from allel.chunked import get_blen_array
from allel.compat import memoryview_safe
from allel.opt.stats import gn_pairwise_corrcoef_int8, gn_pairwise2_corrcoef_int8, \
gn_... | mit | -6,201,206,898,779,084,000 | 31.017301 | 84 | 0.590727 | false |
ecotox/pacfm | pacfm/controller/tools/circos/building/assembler.py | 1 | 3304 | from collections import OrderedDict
from pandas import DataFrame
from pacfm.model import Coordinate, Chromosome, Ideogram
from pacfm.model import LinkCoordinate
class Assembler(object):
"""
assembles the circos abundance map structure.
biodb_selector: biodb.Selector instance
abundance... | mit | -4,182,199,072,962,714,000 | 29.036364 | 79 | 0.537228 | false |
foreversand/QSTK | Examples/Validation.py | 1 | 5524 | '''
(c) 2011, 2012 Georgia Tech Research Corporation
This source code is released under the New BSD license. Please see
http://wiki.quantsoftware.org/index.php?title=QSTK_License
for license details.
Created on February, 9, 2013
@author: Sourabh Bajaj
@contact: sourabhbajaj@gatech.edu
@summary: Python Validation Scr... | bsd-3-clause | 5,958,295,362,151,716,000 | 29.351648 | 86 | 0.708726 | false |
bsautermeister/machine-learning-examples | visualization/keras/vgg16_visualize_convnet_activation_heatmap.py | 1 | 4158 | import argparse
import os
import sys
import cv2
import matplotlib.pyplot as plt
import numpy as np
from tensorflow.contrib.keras import applications
from tensorflow.contrib.keras import backend as K
from tensorflow.contrib.keras import preprocessing
import cnn_classification.keras.dogs_cats_dataset as dataset
import ... | mit | -6,352,257,524,204,803,000 | 33.363636 | 118 | 0.669072 | false |
huazhisong/race_code | baidu_xijiao/codes/input_helper.py | 1 | 8436 | # 100中图片
# %%
from sklearn.preprocessing import label_binarize
import tensorflow as tf
import numpy as np
import os
# %%
file = 'train_data.txt'
# change data to real predictions
def get_real_label(data, file = 'train_data.txt', trainable=True):
'''
Args:
data: predi
Returns:
list of images... | gpl-3.0 | 9,115,338,627,568,042,000 | 33.54918 | 97 | 0.539739 | false |
MartinThoma/algorithms | ML/movielens-20m/ml-20m/movies_analysis.py | 1 | 2395 | from collections import Counter
from itertools import combinations
import clana.io
import clana.visualize_cm
import networkx as nx
import numpy as np
import pandas as pd
import progressbar
# Load the data
df = pd.read_csv("movies.csv")
df["genres"] = df["genres"].str.split("|")
# Analyze the data
list_values = [valu... | mit | 2,289,728,226,151,431,200 | 29.705128 | 87 | 0.65929 | false |
cython-testbed/pandas | pandas/tseries/offsets.py | 1 | 81716 | # -*- coding: utf-8 -*-
from datetime import date, datetime, timedelta
import functools
import operator
from pandas.compat import range
from pandas import compat
import numpy as np
from pandas.core.dtypes.generic import ABCPeriod
from pandas.core.tools.datetimes import to_datetime
import pandas.core.common as com
# ... | bsd-3-clause | 8,722,054,524,984,704,000 | 32.231395 | 79 | 0.557431 | false |
dr-leo/pandaSDMX | pandasdmx/tests/test_insee.py | 1 | 4267 | # TODO tidy these tests to use fixtures/methods from pandasdmx.tests
from collections import OrderedDict
import pytest
import pandasdmx
from pandasdmx import Request
from .data import BASE_PATH as test_data_path
test_data_path = test_data_path / "INSEE"
DATAFLOW_FP = test_data_path / "dataflow.xml"
DATASETS = {
... | apache-2.0 | -5,387,207,897,127,990,000 | 31.325758 | 88 | 0.597141 | false |
jenniyanjie/sg-stock-related | version3/jsonwebretrieve.py | 1 | 2109 | import os, re, sys, time, datetime, copy, calendar
import pandas, pdb
import simplejson as json
from pattern.web import URL, extension, cache, plaintext, Newsfeed
class WebJsonRetrieval(object):
"""
General object to retrieve json file from the web.
Would require only the first tag so after that c... | mit | -1,144,586,067,000,230,100 | 29.57971 | 84 | 0.573732 | false |
twhyntie/coding-challenges | cernatschool/helpers.py | 1 | 9886 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#...for the logging.
import logging as lg
#...for the MATH.
import numpy as np
#...for the data analysis.
import pandas as pd
#...for the least squares stuff.
from scipy.optimize import leastsq
#...for the plotting.
import pylab as plt
#...for the colours.
from matplo... | apache-2.0 | -2,826,983,471,519,716,400 | 28.598802 | 139 | 0.553308 | false |
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