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def flatten_json(nested_json):
    """
        Flatten json object with nested keys into a single level.

        Args:
            nested_json: A nested json object.

        Returns:
            The flattened json object if successful, None otherwise.
    """

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def get_matches_df(sparse_matrix, name_vector, top=100):
    non_zeros = sparse_matrix.nonzero()
    
    sparserows = non_zeros[0]
    sparsecols = non_zeros[1]
    
    if top:
        nr_matches = top
    else:
        nr_matches = sparsecols.size

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from itertools import chain, starmap

def flatten_json_iterative_solution(dictionary):
    """Flatten a nested json file"""

    def unpack(parent_key, parent_value):
        """Unpack one level of nesting in json file"""
        # Unpack one level only!!!
        
        if isinstance(parent_value, dict):

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from scipy.sparse import csr_matrix
!pip install sparse_dot_topn 
import sparse_dot_topn.sparse_dot_topn as ct

def awesome_cossim_top(A, B, ntop, lower_bound=0):
    # force A and B as a CSR matrix.
    # If they have already been CSR, there is no overhead
    A = A.tocsr()
    B = B.tocsr()
    M, _ = A.shape

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import plotly.graph_objects as go

fig = go.Figure(data=go.Scattergeo(
    lat = df['latitude'],
    lon = df['longitude'],
    text = df['_id'],
    marker = dict(
            size = 8,
            opacity = 0.7,
            reversescale = True,

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# Encourage lander to use as little fuel as possible
# i.e. 0.85, or 0.32
fuel_conservation = fuel_remaining / total_fuel 

if distance_to_goal is decreasing:
   if speed < threshold:
       if position is on landing pad:
           # Land successfully; give a big reward
           landing_reward = 100
           # Multiply percentage of remaining fuel

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STOPWORDS = stopwords.words('english')
STOPWORDS = set(STOPWORDS)
    
def text_prepare(text, STOPWORDS):
    """
        text: a string
        
        return: a clean string
    """
    REPLACE_BY_SPACE_RE = re.compile('[\n\"\'/(){}\[\]\|@,;#]')

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###

This season reminds me of the day I met you! You are my best colleague. Thank you!

###

We have surely come a long way! Happy Christmas my friend.

###

alinazhanguwo

Christmas Wishes for Colleagues

###
You have worked very hard this year. You really deserve to have a wonderful Christmas. Merry Christmas my colleague.

###
It has always been a pleasure working with you! I wish you a Merry Christmas!

###
It feels great working with someone as knowledgeable as you and yet so humble. I wish you a Merry Christmas!

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fig1, (ax1, ax2) = plt.subplots(1,2, figsize=(12,8), sharey=False)
fig1.tight_layout() 
fig1.subplots_adjust(top=0.86)

sns.set_color_codes("pastel")
sns.barplot(x="Deaths", y="Province/State", data=bar_plot_df, label="num of Deaths", color="b", ax=ax1)

ax1.legend(ncol=2, loc="lower left", frameon=True)
ax1.set(xlim=(0, 33323), ylabel="", xlabel="Num of Deaths by states")
sns.despine(left=True, bottom=True,ax=ax1)