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12.1k
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ax.legend(loc='upper left')
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all(dict.values())
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a = re.compile('p(?:resent|eople)')
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zipfile.ZipFile(zipbytes)
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del L[index]
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subprocess.call(['php', 'path/to/script.php'])
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zip(*elements)[1]
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list(d.values())
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l3 = [x for x in l1 if x not in l2]
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x.pop(random.randrange(len(x)))
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globals()
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print('hello')
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l = request.user.groups.values_list('name', flat=True)
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df.loc[:, (slice(None), 'A')]
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f.set_size_inches(11.69, 8.27)
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cur.callproc('my_stored_proc', (first_param, second_param, an_out_param))
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new_dict = {k: my_dict[k] for k in my_list if k in my_dict}
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return Response(json_string)
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df.drop(['TMP'], axis=1, inplace=True)
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df1.sort(['a', 'b'], ascending=[True, False])
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[[[flatten[int(i * 2)]]] for i in range(int(len(flatten) / 2))]
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super(UsuarioForm, self).__init__(*args, **kwargs)
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{tuple(x) for x in l1}.intersection(map(tuple, l2))
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{'List of things': ['Alice', 'Bob', 'Evan']}
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[[int(j) for j in i] for i in a]
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sorted(l, key=lambda s: (s.isdigit(), s))
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grouped = df.groupby(level='DATE')
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file.write('first line\n')
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a.__setitem__(slice(0, 1), [1])
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ax.set_title('Title for second plot')
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pd.concat([pd.Series(initial_value), cum_growth]).reset_index(drop=True)
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ax.xaxis.set_major_formatter(dates.DateFormatter('%H:%M'))
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[i for i in my_list if all(x not in i for x in ['91', '18'])]
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f.write('%d' % number)
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lst.append(os.path.splitext(x)[0])
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print(f.read())
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ax.axes.get_xaxis().set_visible(False)
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array([[1, 3, 4, 1], [1, 2, 3, 2], [1, 2, 1, 3]])
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session.delete(instance)
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['{}_{}'.format(k, v) for k, v in list(d.items())]
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ndb.KeyProperty(kind='Foo', required=True)
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print(list(combinations(['hel', 'lo', 'bye'], 2)))
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initgstreamer()
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a = a.reshape((a.shape[0], -1, n))
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mergedgroupdict('(?P<b>.b.)|(?P<i>.i.)', 'abcdefghijk'[::-1])
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r = requests.post(url, files=files, data=data, headers=headers)
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[[0, 0], [1, 1]]
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session.commit()
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pd.to_datetime(pd.Series(['05/23/2005']), format='%m/%d/%Y')
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cursor = db.cursor(dictionary=True)
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driver.execute_script('window.scrollTo(0, document.body.scrollHeight);')
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df.corr().ix[('special_col'), :-1]
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all_data.append(data)
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pobj.stdin.flush()
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global_dict['bar'] = 'hello'
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s.reset_index(drop=True, inplace=True)
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np.any(my_array[:, (0)] == value)
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cv2.imshow('image', im)
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print(celery.current_task.task_id)
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parser.add_argument('input2', nargs='+', type=int)
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print(text.encode().decode('unicode-escape'))
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example2()
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a = re.compile('p(?:resent)')
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random_key = os.urandom(16)
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[item for item in lis if item[1] not in seen and not seen.add(item[1])]
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list(range(0, 10, 3))
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lines.sort()
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super(ConcurrentModel, self).save(*args, **kwargs)
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win.show_all()
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""",""".join(map(str, li2))
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print(alphs[:i] + alphs[i::-1])
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pd.crosstab(df.A, df.B).apply(lambda r: r / r.sum(), axis=1)
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df1.apply(lambda s: df2.corrwith(s))
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driver.execute_script('%s' % js)
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[0, 0, 0, 0, 0, 0, 0, 0, 0],
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df2[df2.Name == 'Joe'].T
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min([x for x in [None, 1, 2] if x is not None])
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l = ['foo', 'bar', 'buz']
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['this', 'day', 'is']
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map(lambda d: d.get('value', 'default value'), l)
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im = Image.open(tempimg)
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xml_soup = BeautifulSoup(xml_object, 'xml')
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print(('Nope, that is not a two. That is a', x))
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L = [c for c in L if c not in ['a', 'c']]
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re.sub('(%)', '\\g<1>\\g<1>', original)
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struct.unpack('>Q', str)
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time.sleep(4)
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myplsda = PLSRegression().fit(X=Xdata, Y=dummy)
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np.random.seed(1)
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s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
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d = dict(itertools.zip_longest(fillvalue='', *([iter(l)] * 2)))
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result.append(b[index])
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Image('img.png').write('clipboard:')
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SCRIPT_ROOT = os.path.dirname(os.path.realpath(__file__))
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re.sub('\\s+', '', 'strip my spaces')
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df['in'].groupby((df['in'] != df['in'].shift()).cumsum()).cumsum()
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procs.append(multiprocessing.Process(target=worker))
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f.close()
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starf = [int(i) for i in starf]
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print('Valid' if re.match('^[a-zA-Z0-9_]*$', word) else 'Invalid')