100+ results results for 'import pandas repo:fomcl/savreaderwriter' (1765 ms)
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_4 | 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/admin-github-cloud/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
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
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
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",
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)
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):
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 """
test_multiclass.py https://gitlab.com/admin-github-cloud/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,
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
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
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
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
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
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
__init__.py https://gitlab.com/pooja043/Globus_Docker_3 | 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
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()
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 ]
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
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",
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
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,)
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_3 | 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
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_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:
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",
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
nlp.py https://gitlab.com/lancezlin/ai | Python | 241 lines
4
5import pandas as pd
6from copy import deepcopy
6from copy import deepcopy
7from sklearn.linear_model import SGDClassifier
8from sklearn.model_selection import GridSearchCV
8from sklearn.model_selection import GridSearchCV
9import re
10import os
10import os
11from sklearn.feature_extraction.text import CountVectorizer
12import nltk
12import nltk
13from nltk.stem.porter import PorterStemmer
14from nltk.corpus import stopwords
prep_covost_data.py https://gitlab.com/lwd17/enhanced_examplar_ae | Python | 279 lines
6
7import argparse
8import logging
9from pathlib import Path
10import shutil
11from tempfile import NamedTemporaryFile
11from tempfile import NamedTemporaryFile
12from typing import Optional, Tuple
13
13
14import pandas as pd
15import torchaudio
15import torchaudio
16from examples.speech_to_text.data_utils import (
17 create_zip,
pandas_sqlite_test.py https://github.com/chromium/chromium.git | Python | 78 lines
8 pass
9import unittest
10
12
13from cli_tools.soundwave import pandas_sqlite
14from core.external_modules import pandas
16
17@unittest.skipIf(pandas is None, 'pandas not available')
18class TestPandasSQLite(unittest.TestCase):
30 def testCreateTableIfNotExists_alreadyExists(self):
31 df = pandas_sqlite.DataFrame(
32 [('bug_id', int), ('summary', str), ('status', str)], index='bug_id')
35 self.assertFalse(pandas.io.sql.has_table('bugs', con))
36 pandas_sqlite.CreateTableIfNotExists(con, 'bugs', df)
37 self.assertTrue(pandas.io.sql.has_table('bugs', con))
adapterbokeh.py https://gitlab.com/oytunistrator/pythalesians | Python | 199 lines
23from bokeh.plotting import figure, output_file, show
24import pandas
25
25
26from pythalesians.graphics.graphs.lowleveladapters.adaptertemplate import AdapterTemplate
27from pythalesians.graphics.graphs.graphproperties import GraphProperties
27from pythalesians.graphics.graphs.graphproperties import GraphProperties
28from pythalesians.util.constants import Constants
29
29
30import numpy
31
53
54 if type(data_frame.index) == pandas.tslib.Timestamp:
55 p1 = figure(
analytics-ipynb.html.md.erb https://gitlab.com/ggsaavedra/PredictionIO | Ruby HTML | 98 lines
33```python
34import pandas as pd
35def rows_to_df(rows):
36 return pd.DataFrame(map(lambda e: e.asDict(), rows))
37from pyspark.sql import SQLContext
38sqlc = SQLContext(sc)
69```python
70import matplotlib.pyplot as plt
71count = map(lambda e: e.c, summary)
index.md https://gitlab.com/github-cloud-corporation/tensorflow | Markdown | 275 lines
46
473. Install the pandas data analysis library. tf.learn doesn't require pandas, but it does support it, and this tutorial uses pandas. To install pandas:
48 1. Get `pip`:
58
59 2. Use `pip` to install pandas:
60
61 ```shell
62 $ sudo pip install pandas
63 ```
65 If you have trouble installing pandas, consult the [instructions]
66(http://pandas.pydata.org/pandas-docs/stable/install.html) on the pandas site.
67
201```python
202import pandas as pd
203import urllib
Devoir2_correction.ipynb https://gitlab.com/gvallverdu/cours-python | Jupyter | 340 lines
21 "* Lire le fichier par vous même en le parcourant ligne par ligne\n",
22 "* Utiliser la fonction read_csv() du module pandas pour lire le tableau.\n",
23 "\n",
155 "source": [
156 "## Partie 2 : lecture du fichier avec pandas\n",
157 "\n",
157 "\n",
158 "Il faut commencer par importer le module pandas :"
159 ]
168 "source": [
169 "import pandas as pd"
170 ]
175 "source": [
176 "On utilise maintenant la fonction [`read_csv()`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html) de pandas pour lire le fichier. Voici les éléments que l'on indique pour lire le fichier :\n",
177 "\n",
test_rplot.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 299 lines
2from pandas.compat import range
3import pandas.util.testing as tm
4from pandas import read_csv
4from pandas import read_csv
5import os
6import nose
8with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
9 import pandas.tools.rplot as rplot
10
251 def test_rplot1(self):
252 import matplotlib.pyplot as plt
253 path = os.path.join(curpath(), 'data/tips.csv')
262 def test_rplot2(self):
263 import matplotlib.pyplot as plt
264 path = os.path.join(curpath(), 'data/tips.csv')
conf.py https://gitlab.com/vectorci/pandas-td | Python | 285 lines
3#
4# Pandas-TD documentation build configuration file, created by
5# sphinx-quickstart on Tue Nov 17 04:30:03 2015.
15
16import sys
17import os
225latex_documents = [
226 (master_doc, 'Pandas-TD.tex', 'Pandas-TD Documentation',
227 'Keisuke Nishida', 'manual'),
255man_pages = [
256 (master_doc, 'pandas-td', 'Pandas-TD Documentation',
257 [author], 1)
269texinfo_documents = [
270 (master_doc, 'Pandas-TD', 'Pandas-TD Documentation',
271 author, 'Pandas-TD', 'One line description of project.',
test_clean_functions.ipynb https://gitlab.com/ReturnDensityEstimation/LongMemoryModel | Jupyter | 393 lines
25 "import data_cleaning as clean\n",
26 "import pandas as pd\n",
27 "import numpy as np\n",
27 "import numpy as np\n",
28 "from BayesianKalman import kalmanfilter as kf"
29 ]
vary.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 339 lines
1"""An array of genomic intervals, treated as variant loci."""
2from __future__ import absolute_import, division, print_function
3
3
4import logging
5
6import numpy as np
7import pandas as pd
8import vcf
9
10from . import gary
11
CalmeToi.py https://gitlab.com/tianzhou2011/talkingdata | Python | 361 lines
7
8import pandas as pd
9import sys
9import sys
10import numpy as np
11import scipy as sp
11import scipy as sp
12import matplotlib.pyplot as plt
13from sklearn.cross_validation import StratifiedKFold, KFold
13from sklearn.cross_validation import StratifiedKFold, KFold
14from sklearn.metrics import log_loss
15from sklearn.cluster import DBSCAN
15from sklearn.cluster import DBSCAN
16from sklearn import metrics as skmetrics
17from sklearn.preprocessing import StandardScaler
synthetic_data.py https://gitlab.com/razhangwei/news-bullying | Python | 489 lines
4import os.path as osp
5import sys
6import time
6import time
7from copy import deepcopy
8
10import numpy as np
11import pandas as pd
12import seaborn.apionly as sns
12import seaborn.apionly as sns
13from numpy.linalg import norm
14from scipy import sparse
24from lib.model.kernels import ExponentialKernel
25from lib.model.mark_density import TextualMarkDensity
26from lib.model.source_identify_model import SourceIdentifyModel
print_version.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 146 lines
28 import statsmodels
29 from statsmodels import version
30 has_sm = True
30 has_sm = True
31 except ImportError:
32 has_sm = False
63 try:
64 import pandas
65 print("pandas: %s (%s)" % (safe_version(pandas, ['version',
74 dirname(dateutil.__file__)))
75 except ImportError:
76 print(" dateutil: not installed")
78 try:
79 import patsy
80 print("patsy: %s (%s)" % (safe_version(patsy),
dataframe_test.py https://gitlab.com/zharfi/GunSafety | Python | 149 lines
17
18from __future__ import absolute_import
19from __future__ import division
19from __future__ import division
20from __future__ import print_function
21
21
22import tensorflow as tf
23
23
24from tensorflow.contrib.learn.python import learn
25from tensorflow.contrib.learn.python.learn.tests.dataframe import mocks
80
81 def test_set_item_pandas(self):
82 # TODO(jamieas)
timeseries_test.py https://github.com/chromium/chromium.git | Python | 247 lines
4
5import datetime
6import unittest
7
8from cli_tools.soundwave import pandas_sqlite
9from cli_tools.soundwave import tables
9from cli_tools.soundwave import tables
10from core.external_modules import pandas
11
70
71@unittest.skipIf(pandas is None, 'pandas not available')
72class TestTimeSeries(unittest.TestCase):
183 with tables.DbSession(':memory:') as con:
184 pandas_sqlite.InsertOrReplaceRecords(con, 'timeseries', timeseries_in)
185 timeseries_out = tables.timeseries.GetTimeSeries(con, test_path)
views.py https://gitlab.com/IPMsim/Virtual-IPM | Python | 368 lines
16
17import os
18import re
19
20import matplotlib.pyplot as plt
21# noinspection PyUnresolvedReferences
21# noinspection PyUnresolvedReferences
22from mpl_toolkits.mplot3d import Axes3D
23import matplotlib.backends.backend_qt5agg
24import numpy as np
25import pandas
26from pandas.errors import ParserError
26from pandas.errors import ParserError
27import PyQt5.QtCore as QtCore
28import PyQt5.QtGui as QtGui
faq.rst https://gitlab.com/0072016/0072016 | ReStructuredText | 277 lines
57
58* `pandas.io <http://pandas.pydata.org/pandas-docs/stable/io.html>`_ to load
59 heterogeneously typed data from various file formats and database protocols
64optimized file format such as HDF5 to reduce data load times. Various libraries
65such as H5Py, PyTables and pandas provides a Python interface for reading and
66writing data in that format.
81
82The contributor should support the importance of the proposed addition with
83research papers and/or implementations in other similar packages, demonstrate
182
183 >>> from leven import levenshtein # doctest: +SKIP
184 >>> import numpy as np
184 >>> import numpy as np
185 >>> from sklearn.cluster import dbscan
186 >>> data = ["ACCTCCTAGAAG", "ACCTACTAGAAGTT", "GAATATTAGGCCGA"]
views.py https://gitlab.com/lidorle/Django-Assignment1 | Python | 109 lines
2from __future__ import unicode_literals
3import pandas as pd
4from django.shortcuts import render
4from django.shortcuts import render
5from .models import Car,Company,PriceList
6from django.http import Http404
6from django.http import Http404
7import json
8from django.core import serializers
8from django.core import serializers
9from django.core.serializers.json import DjangoJSONEncoder
10from django.views.decorators.csrf import csrf_exempt
10from django.views.decorators.csrf import csrf_exempt
11import urlparse
12from django.http import HttpResponse
LibFMFeatures.py https://gitlab.com/xbsd/kaggle-1 | Python | 191 lines
1import string
2from string import lower
3
4import numpy as np
5from sklearn.feature_extraction import DictVectorizer
6from sklearn.feature_extraction.text import TfidfVectorizer
7from sklearn import preprocessing
8from sklearn_pandas import DataFrameMapper
9from sklearn.datasets.svmlight_format import dump_svmlight_file
10from algo.base_mode import BaseModel
11from sklearn_pandas import DataFrameMapper
12from common.utils import FILE_SEPERATOR
12from common.utils import FILE_SEPERATOR
13from sklearn import pipeline
14from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer
timeseriesio.py https://gitlab.com/oytunistrator/pythalesians | Python | 388 lines
21
22import pandas
23import codecs
23import codecs
24import datetime
25from dateutil.parser import parse
25from dateutil.parser import parse
26import shutil
27
27
28from openpyxl import load_workbook
29import os.path
30
31from pythalesians.util.constants import Constants
32from pythalesians.util.loggermanager import LoggerManager
calculate_path.py https://gitlab.com/mdornfe1/busy_cab | Python | 174 lines
1import sqlalchemy as sa
2import psycopg2
2import psycopg2
3import pandas.io.sql as sqlio
4import pandas as pd
4import pandas as pd
5import matplotlib.pyplot as plt
6import numpy as np
6import numpy as np
7import folium
8import json
8import json
9import requests
10from IPython import embed
10from IPython import embed
11import datetime
12from folium import plugins
test_with_sklearn.py https://gitlab.com/admin-github-cloud/xgboost | Python | 300 lines
1import numpy as np
2import random
10 tm._skip_if_no_sklearn()
11 from sklearn.datasets import load_digits
12 from sklearn.cross_validation import KFold
28 tm._skip_if_no_sklearn()
29 from sklearn.datasets import load_iris
30 from sklearn.cross_validation import KFold
55
56def test_feature_importances():
57 tm._skip_if_no_sklearn()
75 # numeric columns
76 import pandas as pd
77 y = pd.Series(digits['target'])
118 from sklearn.grid_search import GridSearchCV
119 from sklearn.datasets import load_boston
120
bk_filter.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 79 lines
1from __future__ import absolute_import
2
2
3import numpy as np
4from scipy.signal import fftconvolve
4from scipy.signal import fftconvolve
5from .utils import _maybe_get_pandas_wrapper
6
51 --------
52 >>> import statsmodels.api as sm
53 >>> dta = sm.datasets.macrodata.load()
60 # Lancosz Sigma Factors np.sinc(2*j/(2.*K+1))
61 _pandas_wrapper = _maybe_get_pandas_wrapper(X, K)
62 X = np.asarray(X)
75 # convolution
76 if _pandas_wrapper is not None:
77 return _pandas_wrapper(X)
PeerAnalysis.py https://gitlab.com/debasishk/PerformanceTest-Monitoring | Python | 286 lines
34from collections import OrderedDict
35import pandas as pd
36import datetime as dt
36import datetime as dt
37import numpy as np
38import matplotlib.pyplot as plt
38import matplotlib.pyplot as plt
39import sys
40
40
41from AnomalyDetection.Univariate.LOF import LOF
42from ...Utils.InitializeOutlierDetectionParams import ModelParams
42from ...Utils.InitializeOutlierDetectionParams import ModelParams
43from AnomalyDetection import MedianAbsoluteDeviation
44from AnomalyDetection import FastFourierTransform
test_enum_add_cases.swift https://gitlab.com/dwiktor/swift | Swift | 233 lines
3
4import StdlibUnittest
5import enum_add_cases
193 -> [AddPayloadToMultiPayload] {
194 return [.Cats(s), .Ponies(s), .Pandas]
195}
207 return 1
208 case .Pandas:
209 return 2
dynamic.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 373 lines
8import util
9import plotting
10
15try:
16 import pandas as pn
17except ImportError:
36 try:
37 import pandas as pn
38 except ImportError:
38 except ImportError:
39 raise ImportError('pandas is required to use this code (for now)')
40
363if __name__ == '__main__':
364 import pandas.util.testing as ptest
365
pd02-pandas-paris.ipynb https://gitlab.com/gvallverdu/cours-python | Jupyter | 392 lines
34 "%matplotlib inline\n",
35 "import pandas as pd\n",
36 "import numpy as np\n",
36 "import numpy as np\n",
37 "import seaborn as sns\n",
38 "import calendar\n",
48 "<div class=\"alert alert-success\" style=\"margin-top:20px\">\n",
49 " <b>Exercice :</b> Lire le fichier <code>place-de-la-nation-co2.csv</code> avec pandas.\n",
50 "</div>\n",
312 "source": [
313 "Le taux de CO2 semble plus important le mercredi, mais la variation est-elle significative ?"
314 ]
328 "<div class=\"alert alert-success\" style=\"margin-top:20px\">\n",
329 " <b>Exercice :</b> Lire le fichier <code>place-de-la-nation-temperature.csv</code> avec pandas.\n",
330 "</div>\n"
mat2nc.py https://gitlab.com/pkormos/phase_python | Python | 193 lines
11
12import netCDF4 as nc
13import numpy as np
13import numpy as np
14from pandas import DataFrame, date_range
15import h5py
29# 'rc.usc-138044', 'rc.usc-d03','rc.usc-j10', 'rc.usc-l21'])
30# ppt = DataFrame(np.transpose(pmat.get("ppt_corrected")), index=date_range('1962-1-1', '2014-12-31 23:00', freq='H'), columns = p_list) # make pandas dataset
31# ppt = ppt.replace('NaN',-9999)
74 'rc.tg.rme-176_tf'])
75rh = DataFrame(np.transpose(rmat.get("rh")), index=date_range('18-Jun-1981 11:00:00', '01-Oct-2014', freq='H'), columns = r_list) # make pandas dataset
76rh = rh.replace('NaN',-9999)
utils.py https://gitlab.com/brenddongontijo/SMI-UnB | Python | 360 lines
1import json
2import matplotlib.dates as mdates
3import matplotlib.patches as mpatches
3import matplotlib.patches as mpatches
4import mpld3
5import numpy
5import numpy
6import pandas
7
7
8from django.utils import timezone
9from django.utils.translation import ugettext as _
9from django.utils.translation import ugettext as _
10from dateutil.relativedelta import relativedelta
11from matplotlib.figure import Figure
ensemble2.ipynb https://gitlab.com/jeongyoonlee/allstate-claims-severity | Jupyter | 256 lines
30 "source": [
31 "from __future__ import division\n",
32 "from scipy.optimize import minimize \n",
32 "from scipy.optimize import minimize \n",
33 "from sklearn.metrics import mean_absolute_error as MAE\n",
34 "from sklearn import base \n",
35 "from sklearn.utils import check_random_state \n",
36 "import pandas as pd\n",
37 "import numpy as np\n",
38 "\n",
39 "from kaggler.data_io import load_data\n",
40 "from const import SEED"
05_pandas_reference.py https://gitlab.com/varunkothamachu/DAT3 | Python | 243 lines
1'''
2Pandas Reference Guide
3
12
13import pandas as pd
14import numpy as np
101
102### IMPORTING DATA ###
103
PaperPainting.py https://gitlab.com/m10774708/dotcode | Python | 309 lines
1from pymongo import MongoClient
2from sklearn import cluster, datasets, preprocessing, metrics
3from sklearn.linear_model import LinearRegression
4from scipy.spatial.distance import cdist
5import scipy
5import scipy
6import numpy as np
7import matplotlib.pyplot as plt
7import matplotlib.pyplot as plt
8import pandas as pd
9import traceback
9import traceback
10import csv
11import os
11import os
12import time
13import datetime
test_cparser.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 407 lines
6from datetime import datetime
7from pandas import compat
8import csv
18from pandas import DataFrame, Series, Index, isnull, MultiIndex
19import pandas.io.parsers as parsers
20from pandas.io.parsers import (read_csv, read_table, read_fwf,
23 assert_series_equal, network)
24import pandas.lib as lib
25from pandas import compat
27
28import pandas.util.testing as tm
29
30from pandas.parser import TextReader
31import pandas.parser as parser
32
grid.py https://gitlab.com/e0/qgrid | Python | 387 lines
1import pandas as pd
2import numpy as np
2import numpy as np
3import uuid
4import os
4import os
5import json
6from numbers import Integral
7
8from IPython.display import display_html, display_javascript
9try:
9try:
10 from ipywidgets import widgets
11except ImportError:
11except ImportError:
12 from IPython.html import widgets
13from IPython.display import display, Javascript
cmdp_collider_config.py https://gitlab.com/dreval/bmdp-python-scripts | Python | 273 lines
11import numpy as np
12import pandas as pd
13import matplotlib
13import matplotlib
14from typing import Mapping, Any
15from scipy.stats import t
17matplotlib.use('PDF')
18from matplotlib import pyplot as plt
19
pyder.py https://gitlab.com/NREL-DER-training/PythonDER | Python | 299 lines
1from __future__ import absolute_import
2from __future__ import division
2from __future__ import division
3from __future__ import print_function
4
4
5import os
6
6
7import copy
8
8
9import pandas as pd
10import networkx as nx
11
12from . import visualize
13from . import templates
data.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 70 lines
37
38from numpy import recfromtxt, column_stack, array
39from statsmodels.datasets import utils as du
39from statsmodels.datasets import utils as du
40from os.path import dirname, abspath
41
53
54def load_pandas():
55 """
63 data = _get_data()
64 return du.process_recarray_pandas(data, endog_idx=0, dtype=float)
65
test_math.py https://gitlab.com/pooja043/Globus_Docker_4 | Python | 67 lines
1import nose
2
4from numpy.random import randn
5import numpy as np
6
6
7from pandas.core.api import Series, DataFrame, date_range
8from pandas.util.testing import assert_almost_equal
8from pandas.util.testing import assert_almost_equal
9import pandas.core.datetools as datetools
10import pandas.stats.moments as mom
10import pandas.stats.moments as mom
11import pandas.util.testing as tm
12import pandas.stats.math as pmath
12import pandas.stats.math as pmath
13import pandas.tests.test_series as ts
14from pandas import ols
test_sklearn.py https://gitlab.com/peter__barnes/work | Python | 109 lines
1import pandas as pd
2import numpy as np
2import numpy as np
3from sklearn.tree import DecisionTreeClassifier
4from sklearn.naive_bayes import GaussianNB
4from sklearn.naive_bayes import GaussianNB
5from sklearn.metrics import confusion_matrix
6from sklearn.metrics import accuracy_score, precision_score, recall_score
test_dividends.py https://gitlab.com/lbennett/zipline | Python | 407 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 ANNOUNCEMENT_FIELD_NAME,
26)
27from zipline.pipeline.data.dividends import (
28 DividendsByAnnouncementDate,
31)
32from zipline.pipeline.factors.events import (
33 BusinessDaysSinceDividendAnnouncement,
feeding_functions.py https://gitlab.com/github-cloud-corporation/tensorflow | Python | 202 lines
16
17from __future__ import absolute_import
18from __future__ import division
18from __future__ import division
19from __future__ import print_function
20
31from tensorflow.python.platform import tf_logging as logging
32from tensorflow.python.training import queue_runner
33
35try:
36 import pandas as pd
37 HAS_PANDAS = True
147 raise TypeError(
148 "data must be either a numpy array or pandas DataFrame if pandas is "
149 "installed; got {}".format(type(data).__name__))
tensorflow_dataframe_test.py https://gitlab.com/github-cloud-corporation/tensorflow | Python | 354 lines
34try:
35 import pandas as pd
36 HAS_PANDAS = True
152 "penguin": list("abcdefghij")})
153 tensorflow_df = df.TensorFlowDataFrame.from_pandas(pandas_df, shuffle=False)
154
163
164 self._assert_pandas_equals_tensorflow(pandas_df,
165 tensorflow_df,
194 default_values=default_values)
195 self._assert_pandas_equals_tensorflow(pandas_df,
196 tensorflow_df,
252
253 self._assert_pandas_equals_tensorflow(pandas_df,
254 tensorflow_df,
trainit.py https://gitlab.com/smartllvlab/cluster-fsl | Python | 194 lines
1import torch
2import argparse
2import argparse
3import pandas as pd
4import os
4import os
5import json
6import pprint
6import pprint
7from src import utils as ut
8
8
9from src import datasets, models
10from src.models import backbones
10from src.models import backbones
11from torch.utils.data import DataLoader
12
climate.py https://gitlab.com/jargnar/climate-portal | Python | 190 lines
38'''
39import os
40import yaml
40import yaml
41import logging
42import StringIO
43import sqlalchemy
44import pandas as pd
45import json
45import json
46from flask import Flask
47from flask import request
47from flask import request
48from flask import make_response
49from flask import send_from_directory
test_consensus_estimates.py https://gitlab.com/lbennett/zipline | Python | 345 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 ACTUAL_VALUE_FIELD_NAME,
35 SID_FIELD_NAME)
36from zipline.pipeline.data import ConsensusEstimates
37from zipline.pipeline.loaders.consensus_estimates import (
39)
40from zipline.pipeline.loaders.blaze import BlazeConsensusEstimatesLoader
41from zipline.pipeline.loaders.utils import (
wyominglib.py https://gitlab.com/rvalenzuela/wyominglib | Python | 416 lines
2 Download and parse wyoming soundings into
3 pandas DataFrames, then store to HDF5 file
4
22 2)
23 import wyominglib as wl
24 wl.download_wyoming(region='samer',
29 3)
30 import wyominglib as wl
31 wl.download_wyoming(region='samer',
37
38import re
39import sys
43import numpy as np
44import pandas as pd
45from bs4 import BeautifulSoup
test_basic.py https://gitlab.com/github-cloud-corporation/xgboost | Python | 209 lines
1# -*- coding: utf-8 -*-
2import numpy as np
3import xgboost as xgb
3import xgboost as xgb
4import unittest
5
143
144 def test_feature_importances(self):
145 data = np.random.randn(100, 5)
158
159 # number of feature importances should == number of features
160 scores1 = bst.get_score()
160 scores1 = bst.get_score()
161 scores2 = bst.get_score(importance_type='weight')
162 scores3 = bst.get_score(importance_type='cover')
plot_and_correct_humidity076.py https://gitlab.com/pkormos/phase_python | Python | 239 lines
9
10import netCDF4 as nc
11import numpy as np
12import matplotlib.pyplot as plt
13from pandas import DataFrame, date_range
14
35pvar = pn.variables["precipitation"]
36ppt = DataFrame(pvar[:], index=date_range('1962-1-1', '2014-12-31 23:00', freq='H'), columns = p_list) # make pandas dataset
37pn.close()
58rvar = rn.variables["relative_humidity"]
59rh = DataFrame(rvar[:], index=date_range('18-Jun-1981 11:00:00', '01-Oct-2014', freq='H'), columns = r_list) # make pandas dataset
60rn.close()
anova.py https://gitlab.com/pooja043/Globus_Docker_2 | Python | 388 lines
1import numpy as np
2from scipy import stats
2from scipy import stats
3from pandas import DataFrame, Index
4from statsmodels.formula.formulatools import (_remove_intercept_patsy,
198 LVL = np.dot(np.dot(L1,robust_cov),L2.T)
199 from scipy import linalg
200 orth_compl,_ = linalg.qr(LVL)
207 r = L1.shape[0]
208 #from IPython.core.debugger import Pdb; Pdb().set_trace()
209 if test == 'F':
304 --------
305 >>> import statsmodels.api as sm
306 >>> from statsmodels.formula.api import ols
367if __name__ == "__main__":
368 import pandas
369 from statsmodels.formula.api import ols
synthetic.py https://gitlab.com/lbennett/zipline | Python | 257 lines
1from itertools import product
2from string import ascii_uppercase
3
4import pandas as pd
5from pandas.tseries.offsets import MonthBegin
5from pandas.tseries.offsets import MonthBegin
6from six import iteritems
7
7
8from .futures import CME_CODE_TO_MONTH
9
classifier.py https://gitlab.com/SplatoonModdingHub/PTVS | Python | 290 lines
39
40from pandas import read_table
41import numpy as np
41import numpy as np
42import matplotlib.pyplot as plt
43
58 # pandas.read_excel instead of read_table
59 #from pandas import read_excel
60 #frame = read_excel(URL)
63 # BlobService.get_blob_to_path() with read_table() or read_excel()
64 #import azure.storage
65 #service = azure.storage.BlobService(ACCOUNT_NAME, ACCOUNT_KEY)
131 # Use 80% of the data for training; test against the rest
132 from sklearn.cross_validation import train_test_split
133 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)
Validation.py https://gitlab.com/gregas/Classwork | Python | 177 lines
42except ImportError:
43 sys.exit("Error : Numpy can not be imported or not installed.")
44print
47try:
48 import matplotlib
49 print "Matplotlib is installed and version is : ", matplotlib.__version__
56try:
57 import pandas
58 print "Pandas is installed and the version used is : ", pandas.__version__
60except ImportError:
61 sys.exit("Error : Pandas can not be imported or not installed.")
62print
88except ImportError:
89 sys.exit("Error : Setuptools can not be imported or not installed.")
90print