winnydejong

"""
The ElementTree documentation shows how to parse XML using XPath:
https://docs.python.org/3.4/library/xml.etree.elementtree.html#example
"""

import xml.etree.ElementTree as ET

root = ET.fromstring(countrydata)

# Top-level elements

snakers4

import os
import re
import sys
import glob
import nltk
import gensim
import numpy as np
import pandas as pd
from tqdm import tqdm
from uuid import uuid4

audy

#!/usr/bin/env python3

import xml.etree.ElementTree as ET
from pprint import pprint
import code

tree = ET.parse('biosample_result.xml')

def expand_blob(blob, attributes={}):
    '''

teldridge11

import matplotlib
import seaborn as sns
import pandas as pd
from scipy.stats import zscore
from sklearn.preprocessing import MinMaxScaler
from sklearn.cluster import DBSCAN
from matplotlib import cm
from datetime import datetime
from dateutil import parser
import json

onlyforbopi

import os
import sys

try:
    import xml.etree.ElementTree as ET
except Exception as e:
    print(str(e))
else:

slogsdon7

from xml.etree import ElementTree

tree = ElementTree.parse('Users.xml')
root = tree.getroot() # <Element 'users' at 0x105f0e950>
#The root is an array/iterator, so child elements can be accessed with array syntax
row = root[0] # <Element 'row' at 0x105f0e9b0>
row.attrib['DisplayName'] # This is how you access attributes directly

data = []
for row in root:

akashpalrecha

moyocoyani

#Canvas
fig,ax = plt.subplots(1,1,figsize=(13,7.5),dpi=100)

#Chart
ax.plot(x,y,color=palette["primary_chart"],
        zorder=2)
ax.scatter(x,y,color=palette["background"],
           edgecolor=palette["primary"],
            s=90,
           zorder=3)

moyocoyani

#Canvas
fig,ax = plt.subplots(1,1,figsize=(13,7.5),dpi=100)

#Chart
ax.plot(x,y,color=palette["primary_chart"],
        zorder=2)
ax.scatter(x,y,color=palette["background"],
           edgecolor=palette["primary"],
            s=90,
           zorder=3)

ksv-muralidhar

from sklearn.datasets import load_wine
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
data = pd.DataFrame(load_wine()["data"],columns=load_wine()["feature_names"])
data.head()