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| import re | |
| import plotly.express as px | |
| import datetime | |
| import plotly.graph_objects as go | |
| import numpy as np | |
| import pandas as pd | |
| import datetime | |
| def clean_text(text): | |
| new_text = text | |
| for rgx_match in ['[A-Z ]+:']: | |
| new_text = re.sub(rgx_match, '', new_text) | |
| return new_text | |
| def prepare_df(df, categories, date_filter): | |
| try: | |
| df.drop(columns=['Unnamed: 0'], inplace=True) | |
| except: | |
| pass | |
| #df['topic_verification'][(df.headline.str.contains('crude', case=False)) | df.body.str.contains('crude', case=False)] = 'Crude Oil' | |
| try: | |
| news_data = df[df['topic_verification'].isin(categories)] | |
| actual_day = datetime.date.today() - datetime.timedelta(days=1) | |
| pattern_del = actual_day.strftime('%b').upper() | |
| filter = news_data['headline'].str.contains(pattern_del) | |
| news_data = news_data[~filter] | |
| # shift column 'C' to first position | |
| first_column = news_data.pop('headline') | |
| # insert column using insert(position,column_name,first_column) function | |
| news_data.insert(0, 'headline', first_column) | |
| news_data['updatedDate'] = pd.to_datetime(news_data['updatedDate'], format='%Y-%m-%d %H:%M:%S%z') | |
| dates = [] | |
| dates.append(datetime.datetime.strftime(date_filter[0], '%Y-%m-%d %H:%M:%S%z')) | |
| dates.append(datetime.datetime.strftime(date_filter[1], '%Y-%m-%d %H:%M:%S%z')) | |
| news_data = news_data[(news_data['updatedDate'] >= dates[0]) & (news_data['updatedDate'] <= dates[1])] | |
| except Exception as E: | |
| print(E) | |
| return news_data | |
| def plot_3dgraph(news_data): | |
| fig = px.scatter_3d(news_data, | |
| x='neutral_score', | |
| y='negative_score', | |
| z='positive_score', | |
| color='positive_score', | |
| hover_name ='headline', | |
| color_continuous_scale='RdBu', | |
| size_max=40, | |
| size='negative_score', | |
| #text='headline', | |
| hover_data='topic_verification') | |
| fig.update_layout( | |
| height=600, | |
| title=dict(text=f"News Sentiments ({datetime.datetime.now().strftime('%d/%m/%y')})<br><sup>Hover cursor on a datapoint to show news title</sup>", | |
| font=dict(size=35), | |
| automargin=False) | |
| ) | |
| fig.update_traces(textfont_size=8) | |
| trace=dict(type='scatter3d', | |
| x=news_data.iloc[[-1]]['neutral_score'], | |
| y=news_data.iloc[[-1]]['negative_score'], | |
| z=news_data.iloc[[-1]]['positive_score'], | |
| mode='markers', | |
| name= 'MEAN OF SELECTED NEWS', | |
| marker=dict(color=[f'rgb({0}, {250}, {200})' for _ in range(25)], | |
| size=10) | |
| ) | |
| fig.add_trace(trace) | |
| return fig |