## 1.导入
import numpy as np
import pandas as pd
import matplotlib as mpl
import os
import math
import glob
import datetime
from matplotlib import pyplot as plt
import matplotlib.dates as mdates
from datetime import datetime,timedelta
from matplotlib.ticker import MultipleLocator, FormatStrFormatter,FixedFormatter
from pathlib import Path
## 2.读取数据
p1 = Path(r"D:\python\fluxcal\data\particle\分组浓度")
FileList_bc = list(p1.glob("*.csv"))
p2 = Path(r"D:\python\fluxcal\data\particle\原始数据\output_particle_index")
FileList_index = list(p2.glob("*.csv"))
bc_ = []
index_1 = []
for subdf in FileList_bc[:]:
BC = pd.read_csv(subdf,sep=',',na_values=["NaN","NAN"],
usecols = ["DateTimewave_tmp"],
index_col=0,header=0,parse_dates=[0])
bc_.append(BC)
for subdf in FileList_index[:]:
index1 = pd.read_csv(subdf,sep=',',na_values=["NaN","NAN"],
usecols = ["DateTimewave_tmp"],
index_col=0,header=0,parse_dates=[0])
index_1.append(index1)
#### 3. 求差集
bcindex = pd.DataFrame(pd.concat(bc_))
bcindex["time_"] = bcindex.index
index_ = pd.DataFrame(pd.concat(index_1))
index_["time_"] = index_.index
diff = index_.index.difference(bcindex.index)
## 4.导出
pd.DataFrame(diff).to_csv("diff_time.csv")
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