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subway.py
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import os
import time
import numpy as np
import pandas as pd
import datetime
from utils import *
start_time = '2000-1-1'
end_time = '2029-12-31'
def test1():
path = os.path.join(data_dir, '地铁'+'.csv')
df = pd.read_csv(path)
t = pd.DatetimeIndex(pd.to_datetime(df['time'], format='%Y-%m-%d'))
beijing = np.array(df['地铁客流量:北京'], dtype=float)
shanghai = np.array(df['地铁客流量:上海'], dtype=float)
guangzhou = np.array(df['地铁客流量:广州'], dtype=float)
shenzhen = np.array(df['地铁客流量:深圳'], dtype=float)
chengdu = np.array(df['地铁客流量:成都'], dtype=float)
xian = np.array(df['地铁客流量:西安'], dtype=float)
zhengzhou = np.array(df['地铁客流量:郑州'], dtype=float)
hefei = np.array(df['地铁客流量:合肥'], dtype=float)
hangzhou = np.array(df['地铁客流量:杭州'], dtype=float)
kunmin = np.array(df['地铁客流量:昆明'], dtype=float)
t1, beijing = get_period_data(t, beijing, start_time, end_time, remove_nan=True)
t2, shanghai = get_period_data(t, shanghai, start_time, end_time, remove_nan=True)
t3, guangzhou = get_period_data(t, guangzhou, start_time, end_time, remove_nan=True)
t4, shenzhen = get_period_data(t, shenzhen, start_time, end_time, remove_nan=True)
t5, chengdu = get_period_data(t, chengdu, start_time, end_time, remove_nan=True)
t6, xian = get_period_data(t, xian, start_time, end_time, remove_nan=True)
t7, zhengzhou = get_period_data(t, zhengzhou, start_time, end_time, remove_nan=True)
t8, hefei = get_period_data(t, hefei, start_time, end_time, remove_nan=True)
t9, hangzhou = get_period_data(t, hangzhou, start_time, end_time, remove_nan=True)
t10, kunmin = get_period_data(t, kunmin, start_time, end_time, remove_nan=True)
t1, beijing = moving_average(t1, beijing, 7)
t2, shanghai = moving_average(t2, shanghai, 7)
t3, guangzhou = moving_average(t3, guangzhou, 7)
t4, shenzhen = moving_average(t4, shenzhen, 7)
t5, chengdu = moving_average(t5, chengdu, 7)
t6, xian = moving_average(t6, xian, 7)
t7, zhengzhou = moving_average(t7, zhengzhou, 7)
t8, hefei = moving_average(t8, hefei, 7)
t9, hangzhou = moving_average(t7, hangzhou, 7)
t10, kunmin = moving_average(t8, kunmin, 7)
plot_seasonality(t1, beijing, title='地铁客流量:北京 7dma')
plot_seasonality(t2, shanghai, title='地铁客流量:上海 7dma')
plot_seasonality(t3, guangzhou, title='地铁客流量:广州 7dma')
plot_seasonality(t4, shenzhen, title='地铁客流量:深圳 7dma')
plot_seasonality(t5, chengdu, title='地铁客流量:成都 7dma')
plot_seasonality(t6, xian, title='地铁客流量:西安 7dma')
plot_seasonality(t7, zhengzhou, title='地铁客流量:郑州 7dma')
plot_seasonality(t8, hefei, title='地铁客流量:合肥 7dma')
# plot_seasonality(t9, hangzhou, title='地铁客流量:杭州 7dma')
plot_seasonality(t10, kunmin, title='地铁客流量:昆明 7dma')
if __name__=="__main__":
test1()