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How to use str_contains method in pandera

Best Python code snippet using pandera_python

compare_mcs_installations.py

Source:compare_mcs_installations.py

...41    )42    schema_withchecks = pa.DataFrameSchema(43        {44            "Company Name": pa.Column(str),45            "MCS certificate number": pa.Column(str, checks=pa.Check.str_contains("-")),46            "Add 1": pa.Column(str),47            "Add2": pa.Column(str, nullable=True),48            "Town": pa.Column(str, nullable=True),49            "County": pa.Column(str, nullable=True),50            "PCode": pa.Column(str, checks=pa.Check.str_length(6, 8)),51            "Solar Thermal": pa.Column(checks=pa.Check.str_contains("YES|NO")),52            "Wind Turbines": pa.Column(checks=pa.Check.str_contains("YES|NO")),53            "Air Source Heat Pumps": pa.Column(checks=pa.Check.str_contains("YES|NO")),54            "Exhaust Air Heat Pumps": pa.Column(checks=pa.Check.str_contains("YES|NO")),55            "Biomass": pa.Column(checks=pa.Check.str_contains("YES|NO")),56            "Solar Photovoltaics": pa.Column(checks=pa.Check.str_contains("YES|NO")),57            "Micro CHP": pa.Column(checks=pa.Check.str_contains("YES|NO")),58            "SolarAssistedHeatPump": pa.Column(checks=pa.Check.str_contains("YES|NO")),59            "GasAbsorptionHeatPump": pa.Column(checks=pa.Check.str_contains("YES|NO")),60            "Ground/Water Source Heat Pump": pa.Column(61                checks=pa.Check.str_contains("YES|NO")62            ),63            "Battery Storage": pa.Column(checks=pa.Check.str_contains("YES|NO")),64            "Eastern Region": pa.Column(checks=pa.Check.str_contains("YES|NO")),65            "East Midlands Region": pa.Column(checks=pa.Check.str_contains("YES|NO")),66            "London Region": pa.Column(checks=pa.Check.str_contains("YES|NO")),67            "North East Region": pa.Column(checks=pa.Check.str_contains("YES|NO")),68            "North West Region": pa.Column(checks=pa.Check.str_contains("YES|NO")),69            "South East Region": pa.Column(checks=pa.Check.str_contains("YES|NO")),70            "South West Region": pa.Column(checks=pa.Check.str_contains("YES|NO")),71            "West Midlands Region": pa.Column(checks=pa.Check.str_contains("YES|NO")),72            "Yorkshire Humberside Region": pa.Column(73                checks=pa.Check.str_contains("YES|NO")74            ),75            "Northern Ireland Region": pa.Column(76                checks=pa.Check.str_contains("YES|NO")77            ),78            "Scotland Region": pa.Column(checks=pa.Check.str_contains("YES|NO")),79            "Wales Region": pa.Column(checks=pa.Check.str_contains("YES|NO")),80            "Effective From": pa.Column(81                checks=[82                    pa.Check(lambda s: s.dt.year >= 1900),83                    pa.Check(lambda s: s.dt.year <= datetime.now().year),84                ]85            ),86            "Consumer Code": pa.Column(str, checks=pa.Check.str_length(3, 4)),87            "Certification Body": pa.Column(str),88        }89    )90    try:91        mcs_installers_no_unspecified = schema_withchecks.validate(92            mcs_installers_no_unspecified, lazy=True93        )...

functions.py

Source:functions.py

...55        return days56#     def filter_input(string input) {57#         input_is_dangerous = true58#         while (input_is_dangerous) {59#             if (str_contains(input, '(')) {60#                 input = str_replace('(', '', input)61#             } else if (str_contains(input, ')')) {62#                 input = str_replace(')', '', input)63#             } else if (str_contains(input, '')) {64#                 input = str_replace('', '', input)65#             } else if (str_contains(input, '{')) {66#                 input = str_replace('{', '', input)67#             } else if (str_contains(input, '}')) {68#                 input = str_replace('}', '', input)69#             } else if (str_contains(input, '[')) {70#                 input = str_replace('[', '', input)71#             } else if (str_contains(input, ']')) {72#                 input = str_replace(']', '', input)73#             } else if (str_contains(input, 'SELECT')) {74#                 input = str_replace('SELECT', '', input)75#             } else if (str_contains(input, '\'')) {76#                 input = str_replace('\'', '', input)77#             } else if (str_contains(input, '"')) {78#                 input = str_replace('"', '', input)79#             } else {80#                 input_is_dangerous = false81#             }82#         }83#         return input84#     }...

main_plot.py

Source:main_plot.py

1import os2import matplotlib.pyplot as plt3from constants import pkl_name, RunParams4from serializer import load5def data_load(alg: str, data_set: str, params: RunParams):6    data, results = pkl_name(alg, data_set, params)7    model = load(results)8    lable = "RMSE-{}-{} - lr={} k={}".format(alg,data_set, params.lr, params.k, params.reg) \9        if alg == 'mf' else\10        "RMSE-{}-{} - k={} lambda={}".format(alg,data_set, params.k, params.reg)11    return model, lable12algs = frozenset(['mf', 'Adam-AutoRec'])13def draw_plots(algs=set({}), data_set='1m', limit=100, minimum_itres=5, str_contains=None, str_exclude=None):14    models = os.listdir('pickle_res/{}'.format(data_set))15    min = 20016    min_params = None17    best_model = None18    for model in models:19        if model == 'old':20            continue21        filename = model.replace(".pkl", "")22        alg, lr, lf, reg = filename.split("_")23        print(filename, str_contains in filename, (str_contains and str_contains in filename) and not (str_exclude and str_exclude in filename))24        if alg in algs or ((str_contains and str_contains in filename) and not (str_exclude and str_exclude in filename)):25            params = RunParams(float(lr), int(lf), float(reg), 0)26            res_init_params, label = data_load(alg, data_set, params)27            y = [r[1] for r in res_init_params]28            x = [r[0] for r in res_init_params]29            if len(y) < minimum_itres:30                continue31            for value in y:32                if value < min:33                    min = value34                    min_params = params35                    best_model = filename36            plt.plot(x[:limit], y[:limit], label=label.replace("Adam-", ""))37    print("best params: {}, {}, {}".format(min, min_params, best_model))38    plt.legend()39    plt.ylabel('RMSE')40    plt.xlabel('Iterations')41    plt.title("Data set: {}, algorithms:{}".format(data_set, list(algs)))42    plt.show()43if __name__ == '__main__':44    # draw_plots(algs=frozenset({'Adam-AutoRec'}), data_set='1m', limit=200)45    # draw_plots(algs=frozenset({'New-AutoRec'}), data_set='1m', limit=200)46    # draw_plots(algs={'mf'}, data_set='1m', limit=200)47    draw_plots(data_set='1m', limit=500, str_contains="Updated")48    # draw_plots(algs=frozenset({}), data_set='100k', limit=400, str_contains="-f")49    # draw_plots(algs={}, data_set='1m', limit=400, str_contains="New-AutoRec-", str_exclude="")50    # draw_plots(algs={}, data_set='100k', limit=400, str_contains="fsigmoid-gselu", str_exclude="")51    # draw_plots(algs=frozenset({'mf'}), data_set='100k', limit=200)52    # draw_plots(algs=frozenset({'mf'}), limit=200)...

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