100+ results results for 'import pandas' (46 ms)
4"""
5from __future__ import division
6
6
7from functools import wraps
8
12from pandas.core.api import DataFrame, Series, notnull
13import pandas._tseries as _tseries
14
14
15from pandas.util.decorators import Substitution, Appender
16
183 """
184 from pandas import Panel
185 from collections import defaultdict
test_moments.py https://github.com/dasfaha/pandas.git | Python | 273 lines
1import unittest
2import nose
3
4from datetime import datetime
5from numpy.random import randn
5from numpy.random import randn
6import numpy as np
7
7
8from pandas.core.api import Series, DataFrame, DateRange
9from pandas.util.testing import assert_almost_equal
9from pandas.util.testing import assert_almost_equal
10import pandas.core.datetools as datetools
11import pandas.stats.moments as moments
11import pandas.stats.moments as moments
12import pandas.util.testing as tm
13
util.py https://github.com/burakbayramli/classnotes.git | Python | 400 lines
1from scipy.optimize import minimize
2import pandas as pd, random
3import numpy as np, datetime
3import numpy as np, datetime
4import scipy.stats
5
run_inversion_gridded2.py https://gitlab.com/flomertens/sph_img | Python | 252 lines
1import os
2import sys
2import sys
3import time
4import shutil
5
6import matplotlib as mpl
7mpl.use('Agg')
9from libwise import scriptshelper as sh
10from libwise import profileutils
11
11
12import sphimg
13import util
15import numpy as np
16import pandas as pd
17
convo_net.py https://gitlab.com/Mounphuix/MNIST | Python | 251 lines
1from __future__ import print_function
2import os
2import os
3import sys
4import timeit
5import numpy as np
6import pandas as pd
7import theano
7import theano
8import theano.tensor as T
9import six.moves.cPickle as pickle
9import six.moves.cPickle as pickle
10from network_layers import LogisticRegression
11from network_layers import HiddenLayer
11from network_layers import HiddenLayer
12from network_layers import LeNetConvPoolLayer
13from utility_functions import load_data
multilinear.py https://gitlab.com/pooja043/Globus_Docker_1 | Python | 329 lines
14from patsy import dmatrix
15import pandas as pd
16from statsmodels.api import OLS
16from statsmodels.api import OLS
17from statsmodels.api import stats
18import numpy as np
56 formula description of the model
57 dataframe : pandas.dataframe
58 dataframe where the model will be evaluated
87 -------
88 summary : pandas.DataFrame
89 a dataframe containing an extract from the summary of the model
119
120 >>> import statsmodels.api as sm
121 >>> data = sm.datasets.longley.load_pandas()
wide_n_deep_tutorial.py https://gitlab.com/github-cloud-corporation/tensorflow | Python | 212 lines
15"""Example code for TensorFlow Wide & Deep Tutorial using TF.Learn API."""
16from __future__ import absolute_import
17from __future__ import division
17from __future__ import division
18from __future__ import print_function
19
19
20import tempfile
21import urllib
22
23import pandas as pd
24import tensorflow as tf
test_indexing.py https://github.com/jseabold/pandas.git | Python | 289 lines
1import numpy as np
2import pytest
3
4import pandas as pd
5from pandas import Categorical, CategoricalIndex, Index, PeriodIndex, Series
5from pandas import Categorical, CategoricalIndex, Index, PeriodIndex, Series
6import pandas._testing as tm
7import pandas.core.common as com
7import pandas.core.common as com
8from pandas.tests.arrays.categorical.common import TestCategorical
9
252def test_mask_with_boolean_na_treated_as_false(index):
253 # https://github.com/pandas-dev/pandas/issues/31503
254 s = Series(range(3))
zmethods.py https://gitlab.com/solstag/abstractology | Python | 253 lines
19
20import pandas
21from pathlib import Path
24
25from ..ioio import ioio
26
34
35and should return a pandas.Series of a scalar dtype and indexed by 'index'.
36"""
123 x_groups = xblocks[xlevel].groupby(xblocks[xlevel])
124 count0 = pandas.Series(index=xblocks[xlevel].unique())
125 count1 = pandas.Series(index=xblocks[xlevel].unique())
239
240 values = pandas.Series(vals, index=pandas.MultiIndex.from_tuples(keys))
241
test_period.py https://github.com/neurodebian/pandas.git | Python | 251 lines
1import numpy as np
2
2
3import pandas as pd
4import pandas.util.testing as tm
4import pandas.util.testing as tm
5import pandas.core.indexes.period as period
6from pandas import Series, period_range, DataFrame, Period
data_utils.py https://gitlab.com/lwd17/enhanced_examplar_ae | Python | 309 lines
7import csv
8import os
9import os.path as op
9import os.path as op
10import zipfile
11from functools import reduce
11from functools import reduce
12from glob import glob
13from multiprocessing import cpu_count
13from multiprocessing import cpu_count
14from typing import Any, Dict, List
15
16import numpy as np
17import pandas as pd
18import sentencepiece as sp
test_categorical.py https://github.com/jreback/pandas.git | Python | 294 lines
4"""
5from io import StringIO
6import os
7
8import numpy as np
9import pytest
10
11from pandas.core.dtypes.dtypes import CategoricalDtype
12
12
13import pandas as pd
14from pandas import Categorical, DataFrame, Timestamp
14from pandas import Categorical, DataFrame, Timestamp
15import pandas._testing as tm
16
test_inference.py https://github.com/pydata/pandas.git | Python | 524 lines
8
9from pandas._libs.tslibs.ccalendar import (
10 DAYS,
12)
13from pandas._libs.tslibs.period import INVALID_FREQ_ERR_MSG
14from pandas.compat import is_platform_windows
15
16from pandas import (
17 DatetimeIndex,
23)
24import pandas._testing as tm
25from pandas.core.arrays import (
30
31import pandas.tseries.frequencies as frequencies
32import pandas.tseries.offsets as offsets
preprocessing.ipynb https://gitlab.com/aakansh9/SPHERE-Challenge | Jupyter | 188 lines
10 "source": [
11 "import pandas as pd\n",
12 "import numpy as np"
128 "source": [
129 "import xgboost"
130 ]
146 "\u001b[1;32m<ipython-input-54-4c763af0299c>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mxgboost\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDMatrix\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfeats\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlabel\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtargets\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
147 "\u001b[1;32m/opt/conda/lib/python3.5/site-packages/xgboost-0.4-py3.5.egg/xgboost/core.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, data, label, missing, weight, silent, feature_names, feature_types)\u001b[0m\n\u001b[0;32m 220\u001b[0m \u001b[0mfeature_names\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 221\u001b[0m feature_types)\n\u001b[1;32m--> 222\u001b[1;33m \u001b[0mlabel\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_maybe_pandas_label\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlabel\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 223\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 224\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mSTRING_TYPES\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
148 "\u001b[1;32m/opt/conda/lib/python3.5/site-packages/xgboost-0.4-py3.5.egg/xgboost/core.py\u001b[0m in \u001b[0;36m_maybe_pandas_label\u001b[1;34m(label)\u001b[0m\n\u001b[0;32m 164\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlabel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mDataFrame\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 165\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlabel\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m>\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 166\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'DataFrame for label cannot have multiple columns'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 167\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 168\u001b[0m \u001b[0mlabel_dtypes\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlabel\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdtypes\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
Command.java https://github.com/RS1999ent/hadoop-common.git | Java | 409 lines
19
20import java.io.FileNotFoundException;
21import java.io.IOException;
21import java.io.IOException;
22import java.io.PrintStream;
23import java.util.ArrayList;
23import java.util.ArrayList;
24import java.util.Arrays;
25import java.util.LinkedList;
25import java.util.LinkedList;
26import java.util.List;
27
27
28import org.apache.commons.logging.Log;
29import org.apache.commons.logging.LogFactory;
test_callable.py https://github.com/neurodebian/pandas.git | Python | 267 lines
4import numpy as np
5import pandas as pd
6import pandas.util.testing as tm
06 - Lesson.ipynb https://bitbucket.org/timoguin/learn-pandas.git | Jupyter | 382 lines
22 "input": [
23 "# Import libraries\n",
24 "from pandas import DataFrame\n",
24 "from pandas import DataFrame\n",
25 "import pandas as pd"
26 ],
35 "input": [
36 "print 'Pandas version: ' + pd.__version__"
37 ],
44 "text": [
45 "Pandas version: 0.13.0\n"
46 ]
google_image_scraper.py https://gitlab.com/Quantza/DeepClassificationBot | Python | 245 lines
5
6from __future__ import absolute_import
7from __future__ import print_function
7from __future__ import print_function
8import os
9import time
9import time
10import re
11import socket
12
13from selenium import webdriver
14from pattern.web import URL, DOM
95 def retrieve_source_fr_html(self, driver):
96 """ Make use of selenium. Retrieve from html table using pandas table.
97
demo.py https://gitlab.com/yaojian/RenjuAI | Python | 177 lines
1# -*- coding: utf-8 -*-
2import os
3import sys
3import sys
4from datetime import datetime
5import numpy as np
5import numpy as np
6import pandas as pd
7
7
8import mail
9
38def prepare_basic_model(date_zone, file_format='pkl'):
39 from mail_preprocess import parallel_preprocess_v2
40 path_prefix = global_dir + "/2015-12-%s_token." + file_format
prep_mtedx_data.py https://gitlab.com/lwd17/enhanced_examplar_ae | Python | 271 lines
6
7import argparse
8import logging
8import logging
9import os
10from pathlib import Path
10from pathlib import Path
11import shutil
12from itertools import groupby
13from tempfile import NamedTemporaryFile
14from typing import Tuple
15
15
16import pandas as pd
17import soundfile as sf
tile.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 297 lines
4
5from pandas.core.api import DataFrame, Series
6from pandas.core.categorical import Categorical
7from pandas.core.index import _ensure_index
8import pandas.core.algorithms as algos
9import pandas.core.common as com
9import pandas.core.common as com
10import pandas.core.nanops as nanops
11from pandas.compat import zip
12
13import numpy as np
14
fix.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 229 lines
1"""Supporting functions for the 'fix' command."""
2from __future__ import absolute_import, division, print_function
3
3
4import logging
5
6import numpy as np
7import pandas as pd
8
8
9from . import params, smoothing
10
prep_covost_data.py https://gitlab.com/lwd17/enhanced_examplar_ae | Python | 294 lines
7import argparse
8import csv
9import logging
9import logging
10import os
11import os.path as op
12import shutil
13from tempfile import NamedTemporaryFile
14from typing import Optional, Tuple
15
16import pandas as pd
17import torchaudio
17import torchaudio
18from examples.speech_to_text.data_utils import (
19 create_zip,
ioio.py https://gitlab.com/solstag/abstractology | Python | 310 lines
21import pickle
22import json
23import gzip
24import lzma
25import pandas
26from pathlib import Path
26from pathlib import Path
27from itertools import chain
28from tempfile import NamedTemporaryFile
55 "module": lzma,
56 "pandas_arg": "xz",
57 },
272 @classmethod
273 def store_pandas(cls, obj, fpath, fmt=None, formatter_args={}):
274 """
example_enhanced_boxplots.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 98 lines
1import numpy as np
2import matplotlib.pyplot as plt
3
4import statsmodels.api as sm
5
9
10data = sm.datasets.anes96.load_pandas()
11party_ID = np.arange(7)
test_pytables.py https://github.com/bergtholdt/pandas.git | Python | 400 lines
1import nose
2import unittest
2import unittest
3import os
4import sys
5
6import numpy as np
7
7
8from pandas import (Series, DataFrame, Panel, LongPanel, DateRange,
9 MultiIndex)
10from pandas.io.pytables import HDFStore
11import pandas.util.testing as tm
12
13try:
14 import tables
15except ImportError:
generate_baseline03.py https://gitlab.com/tianzhou2011/talkingdata | Python | 397 lines
8import keras
9import pandas as pd
10import os
10import os
11import sys
12import gc
12import gc
13from random import shuffle
14from scipy import sparse
16from sklearn.cross_validation import train_test_split
17from sklearn.metrics import log_loss
18
380 ##################
381 from sklearn.datasets import dump_svmlight_file
382 # Metric
regression.py https://gitlab.com/SplatoonModdingHub/PTVS | Python | 303 lines
44
45from pandas import read_table
46import numpy as np
46import numpy as np
47import matplotlib.pyplot as plt
48
50 # [OPTIONAL] Seaborn makes plots nicer
51 import seaborn
52except ImportError:
63 # pandas.read_excel instead of read_table
64 #from pandas import read_excel
65 #frame = read_excel(URL)
131 # Normalize the entire data set
132 from sklearn.preprocessing import StandardScaler, MinMaxScaler
133 arr = MinMaxScaler().fit_transform(arr)
ReverseTrainSecondLayer.py https://gitlab.com/hyeonjik420/deep_learning_transcriptomics | Python | 86 lines
1from keras.layers import Input, Dense, Activation
2import numpy as np
3from keras.models import Model, load_model
4from keras import optimizers, activations
5import math
6from numpy import *
7import pandas as pd
8from keras.callbacks import ModelCheckpoint
8from keras.callbacks import ModelCheckpoint
9from keras.callbacks import CSVLogger
10from keras import optimizers
10from keras import optimizers
11import tensorflow as tf
12from keras.backend import tensorflow_backend as K
12from keras.backend import tensorflow_backend as K
13import glob
14def sigmo(x):
numeric.py https://github.com/hoffstein/pandas.git | Python | 393 lines
1import numpy as np
2import pandas.lib as lib
3import pandas.algos as _algos
3import pandas.algos as _algos
4import pandas.index as _index
5
6from pandas import compat
7from pandas.indexes.base import Index, InvalidIndexError
8from pandas.util.decorators import Appender, cache_readonly
8from pandas.util.decorators import Appender, cache_readonly
9import pandas.core.common as com
10from pandas.core.common import is_dtype_equal, isnull
10from pandas.core.common import is_dtype_equal, isnull
11import pandas.indexes.base as ibase
12
test_ufunc.py https://github.com/jreback/pandas.git | Python | 304 lines
1from collections import deque
2import string
3
4import numpy as np
5import pytest
6
7import pandas as pd
8import pandas._testing as tm
8import pandas._testing as tm
9from pandas.arrays import SparseArray
10
181 a1, a2 = arrays_for_binary_ufunc
182 # work around https://github.com/pandas-dev/pandas/issues/26987
183 a1[a1 == 0] = 1
298def test_outer():
299 # https://github.com/pandas-dev/pandas/issues/27186
300 s = pd.Series([1, 2, 3])
goes.py https://github.com/ayshih/sunpy.git | Python | 317 lines
8import matplotlib.dates as mdates
9import matplotlib.ticker as mticker
10import numpy as np
10import numpy as np
11import packaging.version
12from matplotlib import pyplot as plt
12from matplotlib import pyplot as plt
13from pandas import DataFrame
14
18import sunpy.io
19from sunpy import log
20from sunpy.extern import parse
159 import sunpy.timeseries
160 import sunpy.data.sample
161 ts_goes = sunpy.timeseries.TimeSeries(sunpy.data.sample.GOES_XRS_TIMESERIES, source='XRS')
FastFourierTransform.py https://gitlab.com/debasishk/PerformanceTest-Monitoring | Python | 328 lines
5import numpy as np
6import pandas as pd
7import matplotlib.pyplot as plt
8import datetime
9# from utils.mkdir import mkdir
10import os
41 out_path (str): The output path where results are stored
42 data (Pandas Dataframe): The input data where Outliers are to be found out
43 test_data (bool): Defaults to False. If model to be used for Unit Tests, explicitely specify this variable as True to bypass get_data() method.
79 Returns:
80 scores (Pandas DataFrame): FFT based outlier scores for each point stored in Pandas DataFrame indexed by tinestamp.
81 """
113 Returns:
114 test_output (Pandas DataFrame): Pandas Dataframe object containing 1 column which holds scores for each point
115 """
common.py https://github.com/neurodebian/pandas.git | Python | 279 lines
2
3import itertools
4from warnings import catch_warnings
4from warnings import catch_warnings
5import numpy as np
6
6
7from pandas.compat import lrange
8from pandas.core.dtypes.common import is_scalar
8from pandas.core.dtypes.common import is_scalar
9from pandas import Series, DataFrame, Panel, date_range, UInt64Index
10from pandas.util import testing as tm
10from pandas.util import testing as tm
11from pandas.io.formats.printing import pprint_thing
12
test_multiclass.py https://gitlab.com/github-cloud-corporation/scikit-learn | Python | 347 lines
1
2from __future__ import division
3import numpy as np
3import numpy as np
4import scipy.sparse as sp
5from itertools import product
6
7from sklearn.externals.six.moves import xrange
8from sklearn.externals.six import iteritems
9
10from scipy.sparse import issparse
11from scipy.sparse import csc_matrix
11from scipy.sparse import csc_matrix
12from scipy.sparse import csr_matrix
13from scipy.sparse import coo_matrix
TextAnalyzer.py https://gitlab.com/vicidroiddev/SouthParkMachineLearning | Python | 302 lines
6import logging
7import pandas
8import numpy as np
8import numpy as np
9import time
10import os
10import os
11import multiprocessing
12import matplotlib.pyplot as plt
19import sknn.mlp
20from sknn.backend import lasagne
21from sklearn.feature_extraction import DictVectorizer
248
249 output = pandas.DataFrame(
250 data={
test_buyback_auth.py https://gitlab.com/lbennett/zipline | Python | 227 lines
3"""
4import blaze as bz
5from blaze.compute.core import swap_resources_into_scope
5from blaze.compute.core import swap_resources_into_scope
6import pandas as pd
7from six import iteritems
8
9from zipline.pipeline.common import(
10 BUYBACK_ANNOUNCEMENT_FIELD_NAME,
19)
20from zipline.pipeline.data import (
21 CashBuybackAuthorizations,
23)
24from zipline.pipeline.factors.events import (
25 BusinessDaysSinceCashBuybackAuth,
tutorials.rst https://github.com/neurodebian/pandas.git | ReStructuredText | 181 lines
11
12pandas own :ref:`10 Minutes to pandas<10min>`
13
61
62- `01 - Lesson: <http://nbviewer.ipython.org/urls/bitbucket.org/hrojas/learn-pandas/raw/master/lessons/01%20-%20Lesson.ipynb>`_
63 - Importing libraries
167
168- `Using Pandas and XlsxWriter to create Excel charts <https://pandas-xlsxwriter-charts.readthedocs.io/>`_
169
176- `Financial analysis in python, by Thomas Wiecki <http://nbviewer.ipython.org/github/twiecki/financial-analysis-python-tutorial/blob/master/1.%20Pandas%20Basics.ipynb>`_
177- `Intro to pandas data structures, by Greg Reda <http://www.gregreda.com/2013/10/26/intro-to-pandas-data-structures/>`_
178- `Pandas and Python: Top 10, by Manish Amde <http://manishamde.github.io/blog/2013/03/07/pandas-and-python-top-10/>`_
178- `Pandas and Python: Top 10, by Manish Amde <http://manishamde.github.io/blog/2013/03/07/pandas-and-python-top-10/>`_
179- `Pandas Tutorial, by Mikhail Semeniuk <http://www.bearrelroll.com/2013/05/python-pandas-tutorial>`_
180- `Pandas DataFrames Tutorial, by Karlijn Willems <http://www.datacamp.com/community/tutorials/pandas-tutorial-dataframe-python>`_
indexing.py https://github.com/hoffstein/pandas.git | Python | 292 lines
1from vbench.benchmark import Benchmark
2from datetime import datetime
5
6common_setup = """from .pandas_vb_common import *
7"""
143try:
144 import pandas.computation.expressions as expr
145except:
161try:
162 import pandas.computation.expressions as expr
163except:
256n=100000
257mdt = pandas.DataFrame()
258mdt['A'] = np.random.choice(range(10000,45000,1000), n)
sql.py https://github.com/rkabir/pandas.git | Python | 443 lines
4"""
5from datetime import datetime
6import numpy as np
6import numpy as np
7import traceback
8
8
9from numpy import NaN
10
10
11from pandas.core.datetools import format, to_datetime
12from pandas.core.api import DataFrame, Series, Index, isnull, pivot
144 def driver(self):
145 import pymssql
146 return pymssql
KalmanFilters.py https://gitlab.com/debasishk/PerformanceTest-Monitoring | Python | 310 lines
6import numpy as np
7from externals.pykalman import KalmanFilter
8import matplotlib.pyplot as plt
8import matplotlib.pyplot as plt
9import pandas as pd
10import datetime, platform, os
11from numpy.random import random
12from utils.mkdir import mkdir
13
23 out_path (str): The output path, to which specific path to be appended to save results
24 data (Pandas Dataframe): The data which needs to be fitted with ARIMA model. Defaults to Empty Dataframe
25 test_data (bool, Optional [Default False]): Defaults to False. If model to be used for Unit Tests, explicitely specify this variable as True to bypass get_data() method.
80 Args:
81 data (Pandas DataFrame): Input Dataset which needs to be smoothed out, and predicted values to be found
82
vectorology.py https://gitlab.com/solstag/abstractology | Python | 259 lines
21 import gensim
22except ImportError:
23 print("Warning: Failed to import `gensim`, some functions may not be available")
24
25import multiprocessing, numpy, os, pandas
26from os import path
26from os import path
27from pathlib import Path
28from collections import OrderedDict
29from itertools import combinations
30from copy import deepcopy
31from matplotlib import pyplot as plt, colors as colors
32
33from .ioio import ioio
34from .corporalogy import Corporalogy
OldVersionCopier.java https://bitbucket.org/cprenzberg/wildfly.git | Java | 239 lines
23
24import static org.junit.Assert.assertNotNull;
25import static org.junit.Assert.assertTrue;
26
27import java.io.BufferedInputStream;
28import java.io.BufferedOutputStream;
28import java.io.BufferedOutputStream;
29import java.io.BufferedReader;
30import java.io.BufferedWriter;
30import java.io.BufferedWriter;
31import java.io.File;
32import java.io.FileInputStream;
32import java.io.FileInputStream;
33import java.io.FileOutputStream;
34import java.io.FileReader;
pivot.py https://github.com/smc77/pandas.git | Python | 291 lines
2
3from pandas import Series, DataFrame
4from pandas.tools.merge import concat
4from pandas.tools.merge import concat
5import pandas.core.common as com
6import numpy as np
6import numpy as np
7import types
8
nanops.py https://github.com/smc77/pandas.git | Python | 382 lines
1import sys
2
2
3import numpy as np
4
5from pandas.core.common import isnull, notnull
6import pandas.core.common as com
7import pandas._tseries as lib
9try:
10 import bottleneck as bn
11 _USE_BOTTLENECK = True
11 _USE_BOTTLENECK = True
12except ImportError: # pragma: no cover
13 _USE_BOTTLENECK = False
128 and sys.version_info[0] >= 3): # pragma: no cover
129 import __builtin__
130 if values.ndim > 1:
test_merge_ordered.py https://github.com/neurodebian/pandas.git | Python | 90 lines
1import pandas as pd
2from pandas import DataFrame, merge_ordered
2from pandas import DataFrame, merge_ordered
3from pandas.util import testing as tm
4from pandas.util.testing import assert_frame_equal
5
6from numpy import nan
7
api.py https://github.com/neurodebian/pandas.git | Python | 81 lines
9from pandas.core.categorical import Categorical
10from pandas.core.groupby import Grouper
11from pandas.io.formats.format import set_eng_float_format
11from pandas.io.formats.format import set_eng_float_format
12from pandas.core.index import (Index, CategoricalIndex, Int64Index,
13 UInt64Index, RangeIndex, Float64Index,
16 PeriodIndex, NaT)
17from pandas.core.indexes.period import Period, period_range, pnow
18from pandas.core.indexes.timedeltas import Timedelta, timedelta_range
24from pandas.core.panel import Panel, WidePanel
25from pandas.core.panel4d import Panel4D
26from pandas.core.reshape.reshape import (
75 def __new__(cls, *args, **kwargs):
76 from pandas.core.resample import TimeGrouper
77 import warnings
test_sorting.py https://github.com/jreback/pandas.git | Python | 284 lines
1import random
2
2
3import numpy as np
4import pytest
5
6from pandas.errors import PerformanceWarning, UnsortedIndexError
7
8from pandas import CategoricalIndex, DataFrame, Index, MultiIndex, RangeIndex
9import pandas._testing as tm
10from pandas.core.indexes.frozen import FrozenList
74 # these are the only two types that perform
75 # pandas compatibility input validation - the
76 # rest already perform separate (or no) such
121def test_unsortedindex_doc_examples():
122 # https://pandas.pydata.org/pandas-docs/stable/advanced.html#sorting-a-multiindex
123 dfm = DataFrame(
AUC_plot.py https://gitlab.com/BudzikFUW/budzik_analiza | Python | 228 lines
1
2import pandas as pd
3import numpy as np
4
5import scipy.stats as st
6import sys
6import sys
7import matplotlib.pyplot as plt
8import os
8import os
9import seaborn as sns
10from itertools import product
10from itertools import product
11from collections import defaultdict
12
misc.py https://gitlab.com/pschuprikov/lpm | Python | 430 lines
1#!/usr/bin/env python3
2from textwrap import dedent
3import math
3import math
4from typing import List, Optional, Tuple, Union, Sequence, NamedTuple
5from sys import stderr
5from sys import stderr
6import os
7import os.path as path
9import click
10import pandas as pd
11import numpy as np
RemoveUnnecessaryCastCodeFixProvider.vb https://gitlab.com/sharadag/Roslyn | Visual Basic | 194 lines
2
3Imports System.Collections.Immutable
4Imports System.Composition
4Imports System.Composition
5Imports System.Threading
6Imports Microsoft.CodeAnalysis.CodeActions
6Imports Microsoft.CodeAnalysis.CodeActions
7Imports Microsoft.CodeAnalysis.CodeFixes
8Imports Microsoft.CodeAnalysis.Diagnostics
8Imports Microsoft.CodeAnalysis.Diagnostics
9Imports Microsoft.CodeAnalysis.Formatting
10Imports Microsoft.CodeAnalysis.Simplification
10Imports Microsoft.CodeAnalysis.Simplification
11Imports Microsoft.CodeAnalysis.Text
12Imports Microsoft.CodeAnalysis.VisualBasic.Syntax
factorplots.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 211 lines
26 x : array-like
27 The `x` factor levels constitute the x-axis. If a `pandas.Series` is
28 given its name will be used in `xlabel` if `xlabel` is None.
43 xlabel : str, optional
44 Label to use for `x`. Default is 'X'. If `x` is a `pandas.Series` it
45 will use the series names.
47 Label to use for `response`. Default is 'func of response'. If
48 `response` is a `pandas.Series` it will use the series names.
49 colors : list, optional
89
90 from pandas import DataFrame
91 fig, ax = utils.create_mpl_ax(ax)
183 """
184 from pandas import Series
185 name = None
test_combine_concat.py https://github.com/neurodebian/pandas.git | Python | 311 lines
9import numpy as np
10import pandas as pd
11
11
12from pandas import Series, DataFrame, date_range, DatetimeIndex
13
13
14from pandas import compat
15from pandas.util.testing import assert_series_equal
15from pandas.util.testing import assert_series_equal
16import pandas.util.testing as tm
17
205 def test_combine_first_dt64(self):
206 from pandas.core.tools.datetimes import to_datetime
207 s0 = to_datetime(Series(["2010", np.NaN]))
sampler.py https://gitlab.com/nexemjail/mir | Python | 223 lines
1import numpy as np
2import librosa
2import librosa
3import scipy
4import scipy.signal
4import scipy.signal
5from math import sqrt
6from math import log
6from math import log
7import scipy.signal.spectral
8
220 #t = time.time()
221 #df = pandas.DataFrame(convert_with_processes(path))
222 #print time.time() - t
PathData.java https://github.com/RS1999ent/hadoop-common.git | Java | 241 lines
20
21import java.io.File;
22import java.io.FileNotFoundException;
22import java.io.FileNotFoundException;
23import java.io.IOException;
24
24
25import org.apache.hadoop.classification.InterfaceAudience;
26import org.apache.hadoop.classification.InterfaceStability;
26import org.apache.hadoop.classification.InterfaceStability;
27import org.apache.hadoop.conf.Configuration;
28import org.apache.hadoop.fs.FileStatus;
28import org.apache.hadoop.fs.FileStatus;
29import org.apache.hadoop.fs.FileSystem;
30import org.apache.hadoop.fs.Path;
pathology.py https://bitbucket.org/davidzhang/camda2013.git | Python | 242 lines
2
3from sklearn.svm import SVC
4from sklearn.ensemble import RandomForestClassifier
4from sklearn.ensemble import RandomForestClassifier
5from sklearn.cross_validation import KFold
6from sklearn.cross_validation import StratifiedKFold
7from sklearn.metrics import roc_curve, auc, precision_score, classification_report
8import pandas as pd
9import numpy as np
9import numpy as np
10from scipy import interp
11import os
11import os
12import pylab as pl
13
test_misc_api.py https://github.com/hoffstein/pandas.git | Python | 343 lines
4import numpy as np
5import pandas as pd
6
6
7from pandas import Index, Series, DataFrame, date_range
8from pandas.tseries.index import Timestamp
9
10from pandas.compat import range
11from pandas import compat
11from pandas import compat
12import pandas.formats.printing as printing
13from pandas.util.testing import (assert_series_equal,
14 ensure_clean)
15import pandas.util.testing as tm
16
install.rst https://github.com/hoffstein/pandas.git | ReStructuredText | 322 lines
156The commands in this table will install pandas for Python 2 from your distribution.
157To install pandas for Python 3 you may need to use the package ``python3-pandas``.
158
165 Debian & Ubuntu, unstable (latest packages), `NeuroDebian <http://neuro.debian.net/index.html#how-to-use-this-repository>`__ , ``sudo apt-get install python-pandas``
166 Ubuntu, stable, `official Ubuntu repository <http://packages.ubuntu.com/search?keywords=pandas&searchon=names&suite=all§ion=all>`__ , ``sudo apt-get install python-pandas``
167 Ubuntu, unstable (daily builds), `PythonXY PPA <https://code.launchpad.net/~pythonxy/+archive/pythonxy-devel>`__; activate by: ``sudo add-apt-repository ppa:pythonxy/pythonxy-devel && sudo apt-get update``, ``sudo apt-get install python-pandas``
167 Ubuntu, unstable (daily builds), `PythonXY PPA <https://code.launchpad.net/~pythonxy/+archive/pythonxy-devel>`__; activate by: ``sudo add-apt-repository ppa:pythonxy/pythonxy-devel && sudo apt-get update``, ``sudo apt-get install python-pandas``
168 OpenSuse & Fedora, stable, `OpenSuse Repository <http://software.opensuse.org/package/python-pandas?search_term=pandas>`__ , ``zypper in python-pandas``
169
194
195 >>> import pandas as pd
196 >>> pd.test()
199 numpy version 1.10.2
200 pandas is installed in pandas
201 Python version 2.7.11 |Continuum Analytics, Inc.|
answer_key.py https://gitlab.com/lbennett/zipline | Python | 341 lines
14# limitations under the License.
15import datetime
16import hashlib
16import hashlib
17import os
18
19import numpy as np
20import pandas as pd
21import pytz
21import pytz
22import xlrd
23import requests
24
25from six.moves import map
26
daterange.py https://github.com/rkabir/pandas.git | Python | 490 lines
2
3from datetime import datetime
4import operator
5
6import numpy as np
7
8from pandas.core.index import Index
9import pandas.core.datetools as datetools
10
334 """
335 import pytz
336
353 Generates a sequence of dates corresponding to the specified time
354 offset. Similar to dateutil.rrule except uses pandas DateOffset
355 objects to represent time increments
UriTemplate.java https://github.com/gkamal/spring-framework.git | Java | 325 lines
18
19import java.io.Serializable;
20import java.io.UnsupportedEncodingException;
20import java.io.UnsupportedEncodingException;
21import java.net.URI;
22import java.net.URISyntaxException;
22import java.net.URISyntaxException;
23import java.util.Collections;
24import java.util.LinkedHashMap;
24import java.util.LinkedHashMap;
25import java.util.LinkedList;
26import java.util.List;
26import java.util.List;
27import java.util.Map;
28import java.util.regex.Matcher;
controller.py https://gitlab.com/shpeely/game-stats | Python | 197 lines
1import logging
2import pandas as pd
3
3
4from game_stats.config import config
5from game_stats.store import StoreFactory
12
13from game_stats.statistics.ultimate_score import UltimateScore
14from game_stats.statistics.game_result_stats import GameResultStats
14from game_stats.statistics.game_result_stats import GameResultStats
15from game_stats.statistics.game_stats import GameStats
16from game_stats.statistics.player_stats import PlayerStats
16from game_stats.statistics.player_stats import PlayerStats
17from game_stats.constants import *
18
external_data.py https://bitbucket.org/aabtzu/mlkaggle.git | Python | 267 lines
2
3import pandas
4import bs4
4import bs4
5import requests
6import urllib3
6import urllib3
7import os
8import datetime
8import datetime
9import argparse
10
25 """
26 df_lines = pandas.read_csv(lines_file)
27 df_lines.Date = pandas.to_datetime(df_lines.Date).dt.date
test_form.py https://gitlab.com/braintech/psychopy-brain | Python | 194 lines
3
4from __future__ import division
5
5
6import os
7import pytest
7import pytest
8from pandas import DataFrame
9from psychopy.visual.window import Window
9from psychopy.visual.window import Window
10from psychopy.visual.form import Form
11from psychopy.visual.text import TextStim
11from psychopy.visual.text import TextStim
12from psychopy.visual.slider import Slider
13from psychopy import constants
plot_partial_dependence.py https://github.com/NelleV/scikit-learn.git | Python | 287 lines
45
46import pandas as pd
47from sklearn.datasets import fetch_california_housing
47from sklearn.datasets import fetch_california_housing
48from sklearn.model_selection import train_test_split
49
73
74from time import time
75from sklearn.pipeline import make_pipeline
95#
96# Importantly, this tabular dataset has very different dynamic ranges for its
97# features. Neural networks tend to be very sensitive to features with varying
103#
104# Note that it is important to check that the model is accurate enough on a
105# test set before plotting the partial dependence since there would be little
__init__.py https://github.com/mblondel/scikit-learn.git | Python | 475 lines
3"""
4from collections import Sequence
5
5
6import numpy as np
7from scipy.sparse import issparse
7from scipy.sparse import issparse
8import warnings
9
9
10from .murmurhash import murmurhash3_32
11from .validation import (as_float_array,
15 check_symmetric)
16from .class_weight import compute_class_weight, compute_sample_weight
17from ..externals.joblib import cpu_count
__init__.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 107 lines
1from __future__ import (absolute_import, division, print_function,
2 unicode_literals)
3
4import warnings
5from contextlib import contextmanager
6
7from matplotlib.cbook import is_string_like, iterable
8from matplotlib import rcParams, rcdefaults, use
15
16# stolen from pandas
17@contextmanager
26
27 >>> import warnings
28 >>> with assert_produces_warning():
78 # it during all of the tests.
79 import locale
80 import warnings
interface.py https://github.com/smc77/pandas.git | Python | 134 lines
1from pandas.core.api import Series, DataFrame, Panel, MultiIndex
2from pandas.stats.ols import OLS, MovingOLS
3from pandas.stats.plm import PanelOLS, MovingPanelOLS, NonPooledPanelOLS
4import pandas.stats.common as common
5
Exercises.ipynb https://gitlab.com/santosh.sivapurapu-ab/pandas_exercises | Jupyter | 179 lines
19 "\n",
20 "### Step 1. Import the necessary libraries"
21 ]
35 "source": [
36 "### Step 2. Import the dataset from this [address](https://raw.githubusercontent.com/guipsamora/pandas_exercises/master/04_Apply/US_Crime_Rates/US_Crime_Rates_1960_2014.csv). "
37 ]
74 "source": [
75 "##### Have you noticed that the type of Year is int64. But pandas has a different type to work with Time Series. Let's see it now.\n",
76 "\n",
plot_and_correct_humidity095b.py https://gitlab.com/pkormos/phase_python | Python | 188 lines
9
10import netCDF4 as nc
11import numpy as np
12import matplotlib.pyplot as plt
13from pandas import Series, date_range
14
29p_list = [p_st.getncattr(tt_list[k]) for k in range(np.shape(pvar)[1])] # sorted rh station list
30ppt = Series(np.ma.filled(pvar[:,p_list.index(stn0)],np.nan).ravel(),index=date_range('1962-1-1', '2014-12-31 23:00', freq='H')) # make pandas dataset
31pn.close()
39r_list = [rh_st.getncattr(tt_list[k]) for k in range(np.shape(rvar)[1])] # sorted rh station list
40rh = Series(np.ma.filled(rvar[:,r_list.index(stn0)],np.nan).ravel(),index=date_range('18-Jun-1981 11:00:00', '01-Oct-2014', freq='H')) # make pandas dataset
41rn.close()
common.py https://github.com/rkabir/pandas.git | Python | 353 lines
8from numpy.lib.format import read_array, write_array
9import numpy as np
10
10
11import pandas._tseries as _tseries
12
34 '''
35 from pandas.core.generic import PandasObject
36 from pandas import Series
120def _default_index(n):
121 from pandas.core.index import NULL_INDEX
122 if n == 0:
141def _ensure_index(index_like):
142 from pandas.core.index import Index
143 if not isinstance(index_like, Index):
Exercises.ipynb https://gitlab.com/santosh.sivapurapu-ab/pandas_exercises | Jupyter | 156 lines
17 "\n",
18 "### Step 1. Import the necessary libraries"
19 ]
33 "source": [
34 "### Step 2. Import the first dataset [cars1](https://raw.githubusercontent.com/guipsamora/pandas_exercises/master/05_Merge/Auto_MPG/cars1.csv) and [cars2](https://raw.githubusercontent.com/guipsamora/pandas_exercises/master/05_Merge/Auto_MPG/cars2.csv). "
35 ]
misc.py https://github.com/hoffstein/pandas.git | Python | 389 lines
1from numpy import NaN
2from pandas import compat
3import numpy as np
4
5from pandas.core.api import Series, DataFrame
6from pandas.core.series import remove_na
7from pandas.compat import zip, lrange
8import pandas.core.common as com
9
ConcurrentTransactionAwareProxyTests.java https://github.com/iboyko/spring-batch.git | Java | 279 lines
18
19import static org.junit.Assert.assertEquals;
20import static org.junit.Assert.assertFalse;
20import static org.junit.Assert.assertFalse;
21import static org.junit.Assert.assertTrue;
22import static org.junit.Assert.fail;
23
24import java.util.ArrayList;
25import java.util.HashMap;
25import java.util.HashMap;
26import java.util.List;
27import java.util.Map;
27import java.util.Map;
28import java.util.Set;
29import java.util.concurrent.Callable;
test_indexing.py https://github.com/pydata/pandas.git | Python | 360 lines
1from datetime import (
2 datetime,
4)
5import re
6
6
7import numpy as np
8import pytest
9
10from pandas import (
11 Index,
20)
21import pandas._testing as tm
22
retrieve_features.py https://gitlab.com/genehack-2/15a.ozerov.team_untitled | Python | 288 lines
1import cv2
2import numpy as np
3from matplotlib import pyplot as plt
4import pandas as pd
5import seaborn as sns
5import seaborn as sns
6import sys
7HOME_DIR = '/Users/agalicina/Term10/genehack/' ##change for your machine
8sys.path.append(HOME_DIR+'genehack2016')
9from process import *
10from sklearn.metrics import roc_curve, auc
10from sklearn.metrics import roc_curve, auc
11import math
12
hashing.py https://github.com/neurodebian/pandas.git | Python | 332 lines
6import numpy as np
7from pandas._libs import hashing, tslib
8from pandas.core.dtypes.generic import (
12 ABCDataFrame)
13from pandas.core.dtypes.common import (
14 is_categorical_dtype, is_list_like)
14 is_categorical_dtype, is_list_like)
15from pandas.core.dtypes.missing import isna
16from pandas.core.dtypes.cast import infer_dtype_from_scalar
75 """
76 from pandas import Series
77 if hash_key is None:
284 if categorize:
285 from pandas import factorize, Categorical, Index
286 codes, categories = factorize(vals, sort=False)
DynamicPricingAlgo .ipynb https://gitlab.com/thiagarajan.saravanan/dynamic-pricer | Jupyter | 496 lines
23 "import numpy as np\n",
24 "import pandas as pd\n",
25 "data = pd.ExcelFile(\"Breakfast.xlsx\")\n",
171 "Method 1\n",
172 "import pandas as pd\n",
173 "from pymongo import MongoClient\n",
210 "import pymongo\n",
211 "import pandas as pd\n",
212 "from pymongo import Connection\n",
220 "import numpy as np\n",
221 "import pandas as pd\n",
222 "\n",
242 "import pymongo\n",
243 "import pandas as pd\n",
244 "#from pymongo import Connection\n",
testing.pyx https://github.com/neurodebian/pandas.git | Cython | 213 lines
2
3from pandas import compat
4from pandas.core.dtypes.missing import isna, array_equivalent
4from pandas.core.dtypes.missing import isna, array_equivalent
5from pandas.core.dtypes.common import is_dtype_equal
6
120 if not isiterable(b):
121 from pandas.util.testing import assert_class_equal
122 # classes can't be the same, to raise error
131 if a.shape != b.shape:
132 from pandas.util.testing import raise_assert_detail
133 raise_assert_detail(
137 if check_dtype and not is_dtype_equal(a, b):
138 from pandas.util.testing import assert_attr_equal
139 assert_attr_equal('dtype', a, b, obj=obj)
timedeltas.py https://github.com/neurodebian/pandas.git | Python | 191 lines
5import numpy as np
6import pandas as pd
7import pandas._libs.tslib as tslib
8
9from pandas.core.dtypes.common import (
10 _ensure_object,
13 is_list_like)
14from pandas.core.dtypes.generic import ABCSeries, ABCIndexClass
15
78 elif isinstance(arg, ABCSeries):
79 from pandas import Series
80 values = _convert_listlike(arg._values, unit=unit,
188 if box:
189 from pandas import TimedeltaIndex
190 value = TimedeltaIndex(value, unit='ns', name=name)
Multithreaded_server.py https://gitlab.com/Angiolillo/SOKE | Python | 348 lines
1from server import Clustering_dirichlet
2from sklearn.naive_bayes import MultinomialNB
3import numpy as np
4import pandas as pd
5import pickle
5import pickle
6from server import Preprocessing
7import threading
7import threading
8import socket
9
test_period.py https://github.com/jreback/pandas.git | Python | 449 lines
5from pandas._libs.tslibs.period import IncompatibleFrequency
6import pandas.util._test_decorators as td
7
7
8from pandas.core.dtypes.base import registry
9from pandas.core.dtypes.dtypes import PeriodDtype
11import pandas as pd
12import pandas._testing as tm
13from pandas.core.arrays import PeriodArray, period_array
50def test_period_array_readonly_object():
51 # https://github.com/pandas-dev/pandas/issues/25403
52 pa = period_array([pd.Period("2019-01-01")])
399
400 from pandas.core.arrays._arrow_utils import ArrowPeriodType
401
dedup_columns.py https://gitlab.com/mbay/bosch | Python | 97 lines
1from subprocess import Popen, PIPE
2import pandas as pd
3import numpy as np
3import numpy as np
4import argparse
5import time
5import time
6from scipy.sparse import csr_matrix
7from sklearn import preprocessing
cell.py https://gitlab.com/abhi1tb/build | Python | 330 lines
12
13# Python stdlib imports
14from copy import copy
14from copy import copy
15import datetime
16import re
18
19from openpyxl.compat import (
20 NUMERIC_TYPES,
23
24from openpyxl.utils.exceptions import IllegalCharacterError
25
40try:
41 from pandas import Timestamp
42 TIME_TYPES = TIME_TYPES + (Timestamp,)
test_alter_axes.py https://github.com/neurodebian/pandas.git | Python | 280 lines
3
4import pytest
5
8import numpy as np
9import pandas as pd
10
10
11from pandas import Index, Series
12from pandas.core.index import MultiIndex, RangeIndex
13
14from pandas.compat import lrange, range, zip
15from pandas.util.testing import assert_series_equal, assert_frame_equal
15from pandas.util.testing import assert_series_equal, assert_frame_equal
16import pandas.util.testing as tm
17
2015_10_26_Distance_effects.ipynb https://gitlab.com/jdebelius/Absloute-Power | Jupyter | 527 lines
19 "source": [
20 "import numpy as np\n",
21 "import matplotlib.pyplot as plt\n",
22 "import scipy\n",
23 "import pandas as pd\n",
24 "import skbio\n",
25 "\n",
26 "import absloute_power.distance as dist"
27 ]
misc.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 386 lines
1from numpy import NaN
2from pandas import compat
3import numpy as np
4
5from pandas.core.api import Series, DataFrame, isnull, notnull
6from pandas.core.series import remove_na
6from pandas.core.series import remove_na
7from pandas.compat import zip
8
test_common.py https://github.com/rkabir/pandas.git | Python | 129 lines
1from pandas import Series, DataFrame
2from pandas.core.common import notnull, isnull
2from pandas.core.common import notnull, isnull
3import pandas.core.common as common
4import pandas.util.testing as tm
5
6import numpy as np
7
125if __name__ == '__main__':
126 import nose
127 nose.runmodule(argv=[__file__,'-vvs','-x','--pdb', '--pdb-failure'],
engine.py https://gitlab.com/debasishk/PerformanceTest-Monitoring | Python | 274 lines
1from dataprep import DataPreparation
2from model_aggregators import ModelAggregation
3from modify_scores import ModifyScores
4import pandas as pd
5from config import *
5from config import *
6from multiprocessing import Process, Manager
7import warnings
7import warnings
8from utils.dbCon import connect_db
9
11
12# import sys
13# out_file = open("output.txt", "a+")
test_index.py https://github.com/pydata/pandas.git | Python | 389 lines
1import numpy as np
2import pytest
3
4from pandas.errors import PerformanceWarning
5
5
6import pandas as pd
7from pandas import (
13)
14import pandas._testing as tm
15
242 # GH 9967
243 from copy import deepcopy
244
test_foreign.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 199 lines
4import os
5import warnings
6from datetime import datetime
10from pandas import DataFrame, isnull
11import pandas.util.testing as ptesting
12
19
20import pandas
21pandas_old = int(pandas.__version__.split('.')[1]) < 9
43def test_genfromdta_pandas():
44 from pandas.util.testing import assert_frame_equal
45 dta = macrodata.load_pandas().data
196if __name__ == "__main__":
197 import nose
198 nose.runmodule(argv=[__file__,'-vvs','-x','--pdb'],
homework2_correction.ipynb https://gitlab.com/gvallverdu/cours-python | Jupyter | 341 lines
21 "* Read the file by yourself by browsing it line by line\n",
22 "* Use the read_csv() function of the pandas module to read the table.\n",
23 "\n",
154 "source": [
155 "## Part 2: read in the file with pandas\n",
156 "\n",
156 "\n",
157 "First, you have to import the pandas module:"
158 ]
165 "source": [
166 "import pandas as pd"
167 ]
172 "source": [
173 "We now use pandas' [`read_csv()`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html) function to read the file. Here are the elements we have to control to read the :\n",
174 "\n",
pandas-0.19.1-seqf.patch https://gitlab.com/argent/portage | Patch | 357 lines
44 from dateutil.relativedelta import relativedelta
45 from pandas.compat import range, iteritems
46@@ -4851,6 +4852,7 @@ class TestDST(tm.TestCase):
213 else:
214diff --git a/pandas/tslib.pyx b/pandas/tslib.pyx
215index d4eaaa0b5..685de214c 100644
242@@ -412,17 +413,7 @@ class Timestamp(_Timestamp):
243 from pandas.tseries.frequencies import to_offset
244 freq = to_offset(freq)
296+ # setup components
297+ pandas_datetime_to_datetimestruct(value, PANDAS_FR_ns, &dts)
298+ dts.ps = self.nanosecond * 1000
329+ # reconstruct & check bounds
330+ value = pandas_datetimestruct_to_datetime(PANDAS_FR_ns, &dts)
331+ if value != NPY_NAT:
test_nth.py https://github.com/neurodebian/pandas.git | Python | 253 lines
1import numpy as np
2import pandas as pd
3from pandas import DataFrame, MultiIndex, Index, Series, isna
3from pandas import DataFrame, MultiIndex, Index, Series, isna
4from pandas.compat import lrange
5from pandas.util.testing import (
9
10from .common import MixIn
11
tabular_comparison.ipynb https://gitlab.com/rldotai/td-variance | Jupyter | 439 lines
10 "source": [
11 "import numpy as np\n",
12 "from numpy.linalg import pinv\n",
13 "\n",
14 "import pandas as pd\n",
15 "\n",
15 "\n",
16 "import networkx as nx\n",
17 "import pydot\n",
17 "import pydot\n",
18 "from IPython.display import Image, display\n",
19 "\n",
19 "\n",
20 "import matplotlib.pyplot as plt\n",
21 "%matplotlib inline\n",
hdfstore_bench.py https://github.com/hoffstein/pandas.git | Python | 278 lines
1from vbench.api import Benchmark
2from datetime import datetime
5
6common_setup = """from .pandas_vb_common import *
7import os
test_interval.py https://github.com/neurodebian/pandas.git | Python | 261 lines
1import pytest
2import numpy as np
2import numpy as np
3import pandas as pd
4
4
5from pandas import Series, DataFrame, IntervalIndex, Interval
6from pandas.compat import product
6from pandas.compat import product
7import pandas.util.testing as tm
8
pkl_utils.py https://github.com/lamblin/Theano.git | Python | 405 lines
6"""
7from __future__ import absolute_import, print_function, division
8import numpy as np
12import tempfile
13import zipfile
14import warnings
19try:
20 from pickle import DEFAULT_PROTOCOL
21except ImportError:
23
24import theano
25from theano import config
83# python 2.
84# This code is taken from Pandas, https://github.com/pydata/pandas,
85# under the same 3-clause BSD license.
generate_e4.py https://gitlab.com/tianzhou2011/talkingdata | Python | 213 lines
1#!/usr/bin/env python
2from __future__ import division
3from scipy import sparse
3from scipy import sparse
4from sklearn.datasets import dump_svmlight_file
5from sklearn.preprocessing import LabelEncoder, OneHotEncoder
5from sklearn.preprocessing import LabelEncoder, OneHotEncoder
6import argparse
7import logging
7import logging
8import numpy as np
9import os
9import os
10import pandas as pd
11import time
join.pyx https://github.com/neurodebian/pandas.git | Cython | 267 lines
2
3cimport numpy as np
4import numpy as np
5
6cimport cython
7from cython cimport Py_ssize_t
8
9np.import_array()
10
10
11from numpy cimport (ndarray,
12 int8_t, int16_t, int32_t, int64_t, uint8_t, uint16_t,
17
18from pandas._libs.algos import groupsort_indexer, ensure_platform_int
19from pandas.core.algorithms import take_nd