Added company financial files

impact_of_company_financial/data/ASIA_ASSET_FINANCE_PLC.csv

+y,net_profit_margin,earnings_per_share
+2014-3,8.1,0.04
+2014-4,7.5,0.01
+2014-5,7.09,0.02
+2014-6,6.7,0.02
+2014-7,12.1,0.05
+2014-8,10.6,0.03
+2014-9,12.3,0.08
+2014-10,12.78,0.01
+2014-11,10.2,0.03
+2014-12,11.32,0.04
+2015-1,11.11,0.02
+2015-2,9.56,0.01
+2015-3,10.98,0.04
+2015-4,10.9,0.03
+2015-5,11.34,0.02
+2015-6,12.99,0.06
+2015-7,12.4,0.01
+2015-8,12.4,0.15
+2015-9,11.63,0.27
+2015-10,13.8,0.23
+2015-11,13.9,0.22
+2015-12,12.27,0.21
+2016-1,11.7,0.23
+2016-2,16.8,0.25
+2016-3,12.66,0.26
+2016-4,15.9,0.21
+2016-5,15.9,0.17
+2016-6,12.4,0.27
+2016-7,8.8,0.23
+2016-8,11,0.34
+2016-9,11.63,0.27
+2016-10,12.6,0.28
+2016-11,12.8,0.32
+2016-12,12.44,0.38
+2017-1,16.6,0.33
+2017-2,11.78,0.21
+2017-3,13.05,0.4
+2017-4,11.9,0.3
+2017-5,12.65,0.28
+2017-6,9.5,0.27
+2017-7,8.9,0.23
+2017-8,7.8,0.21
+2017-9,7.82,0.19
+2017-10,5.8,0.17
+2017-11,6.9,0.21
+2017-12,7.43,0.22
+2018-1,6.9,0.27
+2018-2,6.5,0.32
+2018-3,8.73,0.27
+2018-4,7.9,0.22
+2018-5,3.8,0.32
+2018-6,2.3,0.08
+2018-7,6.8,0.28
+2018-8,6.3,0.67
+2018-9,3.26,0.85
+2018-10,1.9,0.32
+2018-11,2.4,0.21
+2018-12,2.51,0.07
+2019-1,5.9,0.32
+2019-2,2.5,0.32
+2019-3,3.51,0.69
+2019-4,5.8,0.32
+2019-5,3.8,0.56
+2019-6,3.13,0.85
+2019-7,3.9,0.32
+2019-8,7.9,0.21
+2019-9,2.74,0.1
+2019-10,6.8,0.32
+2019-11,3.8,0.21
+2019-12,3.59,1.02

impact_of_company_financial/data/ASIA_ASSET_FINANCE_PLC_earnings_per_share.csv

+y,ds
+2022-03,0.04
+2022-04,0.01
+2022-05,0.02
+2022-06,0.02
+2022-07,0.05
+2022-08,0.03
+2022-09,0.08
+2022-10,0.01
+2022-11,0.03
+2022-12,0.04
+2022-01,0.02
+2022-02,0.01
+2022-03,0.04
+2022-04,0.03
+2022-05,0.02
+2022-06,0.06
+2022-07,0.01
+2022-08,0.15
+2022-09,0.27
+2022-10,0.23
+2022-11,0.22
+2022-12,0.21
+2022-01,0.23
+2022-02,0.25
+2022-03,0.26
+2022-04,0.21
+2022-05,0.17
+2022-06,0.27
+2022-07,0.23
+2022-08,0.34
+2022-09,0.27
+2022-10,0.28
+2022-11,0.32
+2022-12,0.38
+2022-01,0.33
+2022-02,0.21
+2022-03,0.4
+2022-04,0.3
+2022-05,0.28
+2022-06,0.27
+2022-07,0.23
+2022-08,0.21
+2022-09,0.19
+2022-10,0.17
+2022-11,0.21
+2022-12,0.22
+2022-01,0.27
+2022-02,0.32
+2022-03,0.27
+2022-04,0.22
+2022-05,0.32
+2022-06,0.08
+2022-07,0.28
+2022-08,0.67
+2022-09,0.85
+2022-10,0.32
+2022-11,0.21
+2022-12,0.07
+2022-01,0.32
+2022-02,0.32
+2022-03,0.69
+2022-04,0.32
+2022-05,0.56
+2022-06,0.85
+2022-07,0.32
+2022-08,0.21
+2022-09,0.1
+2022-10,0.32
+2022-11,0.21
+2022-12,1.02
\ No newline at end of file

impact_of_company_financial/data/ASIA_ASSET_FINANCE_PLC_net_profit_margin.csv

+y,ds
+2022-03,8.1
+2022-04,7.5
+2022-05,7.09
+2022-06,6.7
+2022-07,12.1
+2022-08,10.6
+2022-09,12.3
+2022-10,12.78
+2022-11,10.2
+2022-12,11.32
+2022-01,11.11
+2022-02,9.56
+2022-03,10.98
+2022-04,10.9
+2022-05,11.34
+2022-06,12.99
+2022-07,12.4
+2022-08,12.4
+2022-09,11.63
+2022-10,13.8
+2022-11,13.9
+2022-12,12.27
+2022-01,11.7
+2022-02,16.8
+2022-03,12.66
+2022-04,15.9
+2022-05,15.9
+2022-06,12.4
+2022-07,8.8
+2022-08,11
+2022-09,11.63
+2022-10,12.6
+2022-11,12.8
+2022-12,12.44
+2022-01,16.6
+2022-02,11.78
+2022-03,13.05
+2022-04,11.9
+2022-05,12.65
+2022-06,9.5
+2022-07,8.9
+2022-08,7.8
+2022-09,7.82
+2022-10,5.8
+2022-11,6.9
+2022-12,7.43
+2022-01,6.9
+2022-02,6.5
+2022-03,8.73
+2022-04,7.9
+2022-05,3.8
+2022-06,2.3
+2022-07,6.8
+2022-08,6.3
+2022-09,3.26
+2022-10,1.9
+2022-11,2.4
+2022-12,2.51
+2022-01,5.9
+2022-02,2.5
+2022-03,3.51
+2022-04,5.8
+2022-05,3.8
+2022-06,3.13
+2022-07,3.9
+2022-08,7.9
+2022-09,2.74
+2022-10,6.8
+2022-11,3.8
+2022-12,3.59
\ No newline at end of file

impact_of_company_financial/data/data1.csv

+y,ds
+2014-03,8.1
+2014-04,7.5
+2014-05,7.09
+2014-06,6.7
+2014-07,12.1
+2014-08,10.6
+2014-09,12.3
+2014-10,12.78
+2014-11,10.2
+2014-12,11.32
+2015-01,11.11
+2015-02,9.56
+2015-03,10.98
+2015-04,10.9
+2015-05,11.34
+2015-06,12.99
+2015-07,12.4
+2015-08,12.4
+2015-09,11.63
+2015-10,13.8
+2015-11,13.9
+2015-12,12.27
+2016-01,11.7
+2016-02,16.8
+2016-03,12.66
+2016-04,15.9
+2016-05,15.9
+2016-06,12.4
+2016-07,8.8
+2016-08,11
+2016-09,11.63
+2016-10,12.6
+2016-11,12.8
+2016-12,12.44
+2017-01,16.6
+2017-02,11.78
+2017-03,13.05
+2017-04,11.9
+2017-05,12.65
+2017-06,9.5
+2017-07,8.9
+2017-08,7.8
+2017-09,7.82
+2017-10,5.8
+2017-11,6.9
+2017-12,7.43
+2018-01,6.9
+2018-02,6.5
+2018-03,8.73
+2018-04,7.9
+2018-05,3.8
+2018-06,2.3
+2018-07,6.8
+2018-08,6.3
+2018-09,3.26
+2018-10,1.9
+2018-11,2.4
+2018-12,2.51
+2019-01,5.9
+2019-02,2.5
+2019-03,3.51
+2019-04,5.8
+2019-05,3.8
+2019-06,3.13
+2019-07,3.9
+2019-08,7.9
+2019-09,2.74
+2019-10,6.8
+2019-11,3.8
+2019-12,3.59
\ No newline at end of file

impact_of_company_financial/data/data2.csv

+y,ds
+2014-03,0.04
+2014-04,0.01
+2014-05,0.02
+2014-06,0.02
+2014-07,0.05
+2014-08,0.03
+2014-09,0.08
+2014-10,0.01
+2014-11,0.03
+2014-12,0.04
+2015-01,0.02
+2015-02,0.01
+2015-03,0.04
+2015-04,0.03
+2015-05,0.02
+2015-06,0.06
+2015-07,0.01
+2015-08,0.15
+2015-09,0.27
+2015-10,0.23
+2015-11,0.22
+2015-12,0.21
+2016-01,0.23
+2016-02,0.25
+2016-03,0.26
+2016-04,0.21
+2016-05,0.17
+2016-06,0.27
+2016-07,0.23
+2016-08,0.34
+2016-09,0.27
+2016-10,0.28
+2016-11,0.32
+2016-12,0.38
+2017-01,0.33
+2017-02,0.21
+2017-03,0.4
+2017-04,0.3
+2017-05,0.28
+2017-06,0.27
+2017-07,0.23
+2017-08,0.21
+2017-09,0.19
+2017-10,0.17
+2017-11,0.21
+2017-12,0.22
+2018-01,0.27
+2018-02,0.32
+2018-03,0.27
+2018-04,0.22
+2018-05,0.32
+2018-06,0.08
+2018-07,0.28
+2018-08,0.67
+2018-09,0.85
+2018-10,0.32
+2018-11,0.21
+2018-12,0.07
+2019-01,0.32
+2019-02,0.32
+2019-03,0.69
+2019-04,0.32
+2019-05,0.56
+2019-06,0.85
+2019-07,0.32
+2019-08,0.21
+2019-09,0.1
+2019-10,0.32
+2019-11,0.21
+2019-12,1.02
\ No newline at end of file

impact_of_company_financial/data/new_data.csv

+Date,sale
+2010/01,20072.25
+2010/02,20028.17
+2010/03,19940.75
+2010/04,20423.67
+2010/05,20614.95
+2010/06,20680.46
+2010/07,20626.36
+2010/08,20966.6
+2010/09,20934.96
+2010/10,21024.8
+2010/11,21100.66
+2010/12,21758.33
+2011/01,21960.22
+2011/02,22312.68
+2011/03,22422.24
+2011/04,22648.72
+2011/05,22542.46
+2011/06,20453.25
+2011/07,31627.11
+2011/08,30990.09
+2011/09,31081.46
+2011/10,31003.29
+2011/11,30309.06
+2011/12,29650.9
+2012/01,29652.25
+2012/02,29813.93
+2012/03,29813.1
+2012/04,29540.8
+2012/05,30115.35
+2012/06,30360.91
+2012/07,30509.01
+2012/08,30328.47
+2012/09,31217.82
+2012/10,30993.57
+2012/11,31248.31
+2012/12,31615.46
+2013/01,31800.11
+2013/02,31904.33
+2013/03,31287.97
+2013/04,31052.27
+2013/05,31110.19
+2013/06,31283.66
+2013/07,31235.26
+2013/08,31072.96
+2013/09,31028.74
+2013/10,31181.2
+2013/11,31378.3
+2013/12,31648.27
+2014/01,31742.73
+2014/02,31627.6
+2014/03,32172.94
+2014/04,32445.19
+2014/05,32603.18
+2014/06,20934.96
+2014/07,21024.8
+2014/08,21100.66
+2014/09,21758.33
+2014/10,21960.22
+2014/11,22312.68
+2014/12,22422.24
+2015/01,22648.72
+2015/02,22542.46
+2015/03,22467.98
+2015/04,22491.88
+2015/05,22708.61
+2015/06,22739.87
+2015/07,22639.13
+2015/08,22492.34
+2015/09,23185.03
+2015/10,23469.52
+2015/11,23393.79
+2015/12,23484.62
+2016/01,22946.38
+2016/02,22766.33
+2016/03,22835.84
+2016/04,22678.19
+2016/05,22372.94
+2016/06,22267.98
+2016/07,22202.92
+2016/08,22105.9
+2016/09,22120.13
+2016/10,22876.81
+2016/11,22962.78
+2016/12,22642.51
+2017/01,22571.13
+2017/02,23314.42
+2017/03,23099.41
+2017/04,23099.41
+2017/05,23099.41
+2017/06,23099.41
+2017/07,23099.41
+2017/08,23099.41
+2017/09,23099.41
+2017/10,23099.41
+2017/11,23099.41
+2017/12,23099.41
+2018/01,23099.41
+2018/02,23099.41
+2018/03,23099.41
+2018/04,23099.41
+2018/05,23099.41
+2018/06,23099.41
+2018/07,23099.41
+2018/08,28906.71
+2018/09,28911.01
+2018/10,29007.18
+2018/11,29120.43
+2018/12,29454.96
+2019/01,29437.66
+2019/02,29817.42
+2019/03,29907.67
+2019/04,30108.33
+2019/05,30094.87
+2019/06,30052.94
+2019/07,30105.56
+2019/08,30018.56
+2019/09,30241.17
+2019/10,31719.12
+2019/11,31603.26
+2019/12,31627.11
+2020/01,30990.09
+2020/02,31081.46
+2020/03,31235.26
+2020/04,31072.96
+2020/05,31028.74
+2020/06,31181.2
+2020/07,31378.3
+2020/08,31648.27
+2020/09,31742.73
+2020/10,31627.6
+2020/11,32546.54
+2020/12,33298.78
\ No newline at end of file

impact_of_company_financial/fbp.py

+from pandas import read_csv
+from pandas import to_datetime
+from pandas import DataFrame
+from prophet import Prophet
+from matplotlib import pyplot
+import json
+import datetime
+from prophet.serialize import model_to_json, model_from_json
+
+
+def train_fbp(company_name):
+    # net profit
+    path = 'impact_of_company_financial/data/' + company_name + '_net_profit_margin.csv'
+    df = read_csv(path, header=0)
+
+    df.columns = ['ds', 'y']
+    df['ds'] = to_datetime(df['ds'])
+
+    model = Prophet()
+
+    model.fit(df)
+
+    future = list()
+    for i in range(1, 13):
+        date = '2022-%02d' % i
+        future.append([date])
+    future = DataFrame(future)
+    future.columns = ['ds']
+    future['ds'] = to_datetime(future['ds'])
+
+    forecast = model.predict(future)
+
+    print(forecast['yhat'][-7:])
+
+    with open('impact_of_company_financial/trained_models/' + company_name + '_net_profit_margin.json', 'w') as fout:
+        json.dump(model_to_json(model), fout)
+
+    # earning per share
+    path = 'data/' + company_name + '_earnings_per_share.csv'
+    df = read_csv(path, header=0)
+
+    df.columns = ['ds', 'y']
+    df['ds'] = to_datetime(df['ds'])
+
+    model = Prophet()
+
+    model.fit(df)
+
+    future = list()
+    for i in range(1, 13):
+        date = '2022-%02d' % i
+        future.append([date])
+    future = DataFrame(future)
+    future.columns = ['ds']
+    future['ds'] = to_datetime(future['ds'])
+
+    forecast = model.predict(future)
+
+    print(forecast['yhat'][-7:])
+
+    with open('trained_models/' + company_name + '_earnings_per_share.json', 'w') as fout:
+        json.dump(model_to_json(model), fout)
+
+
+def forecast_fbp(company_name, no_of_months):
+    path_net_profit_margin = 'impact_of_company_financial/data/' + company_name + '_net_profit_margin.csv'
+    df_net_profit_margin = read_csv(path_net_profit_margin, header=0)
+
+    path_earnings_per_share = 'impact_of_company_financial/data/' + company_name + '_earnings_per_share.csv'
+    df_earnings_per_share = read_csv(path_earnings_per_share, header=0)
+
+    df_net_profit_margin.columns = ['ds', 'y']
+    df_net_profit_margin['ds'] = to_datetime(df_net_profit_margin['ds'])
+
+    df_earnings_per_share.columns = ['ds', 'y']
+    df_earnings_per_share['ds'] = to_datetime(df_earnings_per_share['ds'])
+
+    model_net_profit_margin = Prophet()
+    model_earnings_per_share = Prophet()
+
+    model_net_profit_margin.fit(df_net_profit_margin)
+    model_earnings_per_share.fit(df_earnings_per_share)
+
+    # with open('trained_models/' + str(company_name) + '_net_profit_margin.json', 'r') as fin:
+    #     model_net_profit_margin = model_from_json(fin.read())
+    #
+    # with open('trained_models/' + str(company_name) + '_earnings_per_share.json', 'r') as fin:
+    #     model_earnings_per_share = model_from_json(fin.read())
+
+    future = list()
+    future_dates = []
+    today = datetime.datetime.today()
+
+    for i in range(no_of_months):
+        today = today + datetime.timedelta(days=30)
+        future.append([today.strftime('%Y-%m')])
+        future_dates.append(today.strftime('%Y-%m'))
+    future = DataFrame(future)
+    future.columns = ['ds']
+    future['ds'] = to_datetime(future['ds'])
+
+    forecast_net_profit_margin = model_net_profit_margin.predict(future)
+    forecast_earnings_per_share = model_earnings_per_share.predict(future)
+
+    data_net_profit_margin = []
+    data_earnings_per_share = []
+
+    for i in forecast_net_profit_margin['yhat'][-no_of_months:]:
+        data_net_profit_margin.append(round(i, 2))
+
+    for i in forecast_earnings_per_share['yhat'][-no_of_months:]:
+        data_earnings_per_share.append(round(i, 2))
+
+    return data_net_profit_margin, data_earnings_per_share, future_dates
+
+
+# train_fbp('ASIA_ASSET_FINANCE_PLC')
+# x,y  = forecast_fbp('ASIA_ASSET_FINANCE_PLC',5)
+
+# print(x,y)
\ No newline at end of file