analysing.py 文件源码

def get_python_guangzhou():
    frame2 = frame[(frame.kd == 'Python') &(frame.city == u'??') ]
    cframe = [v for k, v in frame2.to_dict(orient='index').items()]
    pattern = r'\d{4}-\d{2}-\d{2}'
    for c in cframe:
        if re.match(pattern, c['published']):
            pass
        else:
            c['published'] = datetime.datetime.utcnow().strftime("%Y-%m-%d")
    df = DataFrame(cframe)
    df['published'] = pd.to_datetime(df['published'])
    mask = (df['published'] > '2016-04-01') & (df['published'] <= '2016-05-02')
    dataframe = df.loc[mask]
    jobframe = pd.crosstab(dataframe.experience, frame.salary, margins=True).sort_values(by='All', ascending=False)
    jobframe = jobframe.drop('All', axis=0).drop('All', axis=1)
    pie_chart = pygal.StackedBar()
    pie_chart.title = u'???python?????'
    pie_chart.x_labels = jobframe.index
    for cit, num in jobframe.iteritems():
        pie_chart.add("%s" % (cit), num)
    pie_chart.render_to_file(os.path.dirname(__file__) + '/chart/guangzhou_salary.svg')