dalian-university/wind-LSTM-v2.0-nwp+rp+环境/test.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# time: 2023/4/11 15:58
# file: test.py
# author: David
# company: shenyang JY
import pandas as pd
import numpy as np
# index = pd.date_range('1/1/2000', periods=9, freq='T')
# series = pd.Series(range(9), index=index)
# df = pd.DataFrame({'value': series})
# series1 = series.resample('3T').sum()
# series2 = series.resample('3T', label='right').sum()
# series3 = series.resample('3T', label='right', closed='right').sum()
# series4 = series.resample('30S').asfreq()
# series5 = series.resample('30S').bfill()
# print(series)
# print(series1)
# print(series2)
# print(series3)
# print(series4)
# print("---", series5)

# x = np.random.randint(1,100,20).reshape((10,2))
# print(x)
# from sklearn.model_selection import train_test_split
#
# x_train, x_test = train_test_split(x, test_size=0.2, random_state=1, shuffle=False)
# print("x_train", x_train)
# print("x_test", x_test)


import numpy as np
import pandas as pd
#创建一组数据
data = {'name': ['John', 'Mike', 'Mozla', 'Rose', 'David', 'Marry', 'Wansi', 'Sidy', 'Jack', 'Alic'],
        'age': [20, 32, 29, np.nan, 15, 28, 21, 30, 37, 25],
        'gender': [0, 0, 1, 1, 0, 1, 0, 0, 1, 1],
        'isMarried': ['yes', 'yes', 'no', 'yes', 'no', 'no', 'no', 'yes', 'no', 'no']}
label = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
df = pd.DataFrame(data, index=label)
print(df.loc[:,'name'])
pass