salary02/data_analysis.py

31 lines
878 B
Python

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime
num_time_step = 501
num_iter = 10
env_data = pd.DataFrame(pd.read_excel('env_data.xlsx', engine='openpyxl', sheet_name=0))
assert env_data.shape[0] == num_iter * (num_time_step + 1), f"{env_data.shape[0]}, {num_iter * (num_time_step + 1)}"
lst_df = []
for i in range(num_iter):
df_tmp = env_data.iloc[i * (num_time_step + 1): (i + 1) * (num_time_step + 1), 1:]
lst_df.append(df_tmp)
lst_column = lst_df[0].columns
for str_col in lst_column:
x = np.arange(num_time_step+1)
for df in lst_df:
y = np.array(df[str_col]).flatten()
plt.xlabel('t')
plt.ylabel(str_col)
plt.plot(x, y)
# plt.show()
# plt.close()
plt.savefig(f"{str_col}-{datetime.today().strftime('%Y-%m-%d')}.pdf", bbox_inches="tight")
plt.close()