CGN_taiyuan_104/tmp/measurepoint.py

# -*- coding: utf-8 -*-
"""
Spyder 编辑器

这是一个临时脚本文件。
"""
import os

import pandas as pd

pd.set_option('chained_assignment', None)

select_cols = ['遥测名称', '遥测别名', '风场', '组件', '风机号', '测点']

origin_col_map = {
    'wind_turbine_number': '风机编号', 'wind_turbine_name': '风机原始名称', 'time_stamp': '时间戳',
    'active_power': '有功功率', 'rotor_speed': '风轮转速', 'generator_speed': '发电机转速', 'wind_velocity': '风速',
    'pitch_angle_blade_1': '桨距角1', 'pitch_angle_blade_2': '桨距角2', 'pitch_angle_blade_3': '桨距角3',
    'cabin_position': '机舱位置', 'true_wind_direction': '绝对风向', 'yaw_error1': '对风角度',
    'set_value_of_active_power': '有功功率设定值', 'gearbox_oil_temperature': '齿轮箱油温',
    'generatordrive_end_bearing_temperature': '发电机驱动端轴承温度',
    'generatornon_drive_end_bearing_temperature': '发电机非驱动端轴承温度', 'cabin_temperature': '机舱内温度',
    'twisted_cable_angle': '扭缆角度', 'front_back_vibration_of_the_cabin': '机舱前后振动',
    'side_to_side_vibration_of_the_cabin': '机舱左右振动', 'actual_torque': '实际力矩', 'given_torque': '给定力矩',
    'clockwise_yaw_count': '顺时针偏航次数', 'counterclockwise_yaw_count': '逆时针偏航次数', 'unusable': '不可利用',
    'power_curve_available': '功率曲线可用', 'required_gearbox_speed': '齿轮箱转速',
    'inverter_speed_master_control': '变频器转速(主控)', 'outside_cabin_temperature': '环境温度',
    'main_bearing_temperature': '主轴承轴承温度',
    'gearbox_high_speed_shaft_bearing_temperature': '齿轮箱高速轴轴承温度',
    'gearboxmedium_speed_shaftbearing_temperature': '齿轮箱中速轴轴承温度',
    'gearbox_low_speed_shaft_bearing_temperature': '齿轮箱低速轴轴承温度',
    'generator_winding1_temperature': '发电机绕组1温度', 'generator_winding2_temperature': '发电机绕组2温度',
    'generator_winding3_temperature': '发电机绕组3温度', 'wind_turbine_status': '风机状态1',
    'wind_turbine_status2': '风机状态2', 'turbulence_intensity': '湍流强度'
}


def save_df(df, name):
    df.to_excel(r'C:\Users\wzl\Desktop\中广核104测点\total' + os.sep + str(name) + '.xlsx', columns=select_cols,
                index=False)


def common_measurepoint(df, name):
    df['风场'] = df['遥测别名'].apply(lambda x: x.split('.')[0])
    df['组件'] = df['遥测别名'].apply(lambda x: x.split('.')[3])
    df['风机号'] = df['遥测别名'].apply(lambda x: x.split('.')[2])
    df['测点'] = df['遥测别名'].apply(lambda x: '.'.join(x.split('.')[4:]))
    save_df(df, name + '测点')
    return df


if __name__ == '__main__':
    df = pd.read_csv(r"D:\data\tmp\12CZYC.csv", encoding='gbk')

    df = df[~ df['遥测别名'].str.contains('Farm')]
    df = df[~ df['遥测别名'].str.contains('Statistics')]

    # 添加右玉处理
    name = '右玉'
    youyu_df = common_measurepoint(df[df['遥测名称'].str.contains(name)], name)

    # 添加平陆处理
    name = '平陆'
    pinglu_df = common_measurepoint(df[df['遥测名称'].str.contains(name)], name)

    # 添加芮城处理
    name = '芮城'
    ruicheng_df = common_measurepoint(df[df['遥测名称'].str.contains(name)], name)

    # 添加盂县处理
    name = '盂县'
    yuxian_df = common_measurepoint(df[df['遥测名称'].str.contains(name)], name)

    # 添加古交处理
    name = '古交'
    gujiao_df = common_measurepoint(df[df['遥测名称'].str.contains(name)], name)

    # 添加石楼处理
    name = '石楼'
    shilou_df = common_measurepoint(df[df['遥测名称'].str.contains(name)], name)

    # 添加阳曲处理
    name = '阳曲'
    yangqu_df = common_measurepoint(df[df['遥测名称'].str.contains(name)], name)

    # 添加西潘处理
    name = '西潘'
    xipan_df = common_measurepoint(df[df['遥测名称'].str.contains(name)], name)

    # 添加马家梁处理
    name = '马家梁'
    majialiang_df = common_measurepoint(df[df['遥测名称'].str.contains(name)], name)

    # 添加富风处理
    name = '富风'
    fufeng_df = common_measurepoint(df[df['遥测名称'].str.contains(name)], name)

    # 添加坡底处理
    name = '坡底'
    podi_df = common_measurepoint(df[df['遥测名称'].str.contains(name)], name)

    # 添加贺家沟处理
    name = '贺家沟'
    hejiagou_df = common_measurepoint(df[df['遥测名称'].str.contains(name)], name)
    # result_df = pd.concat([youyu_df, pinglu_df, ruicheng_df, yuxian_df, gujiao_df, shilou_df])