# csvファイル
fpath_csv = r"./TKC/2022/06/28/202206281200.csv"
# csvファイルをdataframeに
df_dt = pd.read_csv(fpath_csv,
skiprows=1,
names = ["date and time","y","x","z","T","C","Q"],
encoding="Shift-JIS"
)
# 列ごとに値を配列に格納
dt_measure = df_dt.loc[:,"date and time"].values
y = df_dt.loc[:,"y"].values
x = df_dt.loc[:,"x"].values
z = df_dt.loc[:,"z"].values
T = df_dt.loc[:,"T"].values
C = df_dt.loc[:,"C"].values
Q = df_dt.loc[:,"Q"].values
X_30 = np.mean(x)
Y_30 = np.mean(y)
Z_30 = np.mean(z)
U_ave30 = np.sqrt(X_30**2 + Y_30**2 + Z_30**2)
# ケルビン表示
T_K = [t + 273.15 for t in T]
# 気温の差の二乗平均リスト
meanlist = []
# 気温の差の二乗平均算出プログラム ラグでループ処理
for j in range(1,len(x)):
sqlist = []
for k in range(len(x)-j):
t2 = (T_K[k]-T_K[k+j])**2
sqlist.append(t2)
meanlist.append(np.mean(sqlist))
