|
@@ -0,0 +1,40 @@
|
|
|
+from datetime import datetime
|
|
|
+
|
|
|
+import pandas as pd
|
|
|
+
|
|
|
+
|
|
|
+def convert_date(date_str):
|
|
|
+ cut_index = str(date_str).rfind("_")
|
|
|
+ date = date_str[0:cut_index].replace("_", "-")
|
|
|
+ time = date_str[cut_index + 1:].replace(":", ".")
|
|
|
+
|
|
|
+ return datetime.strptime(f"{date} {time}", '%Y-%m-%d %H.%M.%S.%f')
|
|
|
+
|
|
|
+
|
|
|
+df = pd.read_csv(r"d:/data/b2_240828_2324_Err 1.csv", header=1)
|
|
|
+df.dropna(subset='TimeStamp', inplace=True)
|
|
|
+df.drop_duplicates(subset='TimeStamp', keep="first", inplace=True)
|
|
|
+
|
|
|
+origin_columns = list(df.columns)
|
|
|
+
|
|
|
+df['TimeStamp1'] = df['TimeStamp'].apply(convert_date)
|
|
|
+df.sort_values(by='TimeStamp1', inplace=True)
|
|
|
+
|
|
|
+# df['DateTime'] = pd.to_datetime(df['TimeStamp'], format="%Y-%m-%d %H:%M:%S")
|
|
|
+df['DateTime'] = df['TimeStamp1'].apply(lambda x: x.strftime("%Y-%m-%d %H:%M:%S"))
|
|
|
+
|
|
|
+print(df.shape)
|
|
|
+
|
|
|
+dateTime_count = df['DateTime'].value_counts()
|
|
|
+
|
|
|
+dateTime_count_1 = dateTime_count[dateTime_count == 1]
|
|
|
+dateTime_count_gt1 = dateTime_count[dateTime_count > 1]
|
|
|
+
|
|
|
+df1 = df[df['DateTime'].isin(dateTime_count_1.index.values)]
|
|
|
+df2 = df[df['DateTime'].isin(dateTime_count_gt1.index.values)]
|
|
|
+
|
|
|
+print(df1.shape)
|
|
|
+print(df2.shape)
|
|
|
+origin_columns.insert(0, 'DateTime')
|
|
|
+df1.to_csv("1秒数据.csv", encoding='utf-8', index=False, columns=origin_columns, date_format="%Y-%m-%d %H:%M:%S.%f")
|
|
|
+df2.to_csv("毫秒数据.csv", encoding='utf-8', index=False, columns=origin_columns, date_format="%Y-%m-%d %H:%M:%S.%f")
|