timestamp

问题 I find the datetime.timestamp() function return different value on Linux and Windows. Here is a simple to to replicate it: from datetime import date, time, datetime, timedelta def main(): dt = datetime(2000, 1, 1) edt = datetime(2006, 12, 31) fname = 't1.csv' f = open(fname, 'w') f.write('date,timestamp\n') while dt <= edt: f.write('{0:%Y-%m-%d},{1:.0f}\n'.format(dt, dt.timestamp())) dt += timedelta(days=1) f.close() return 0 Here is the LAST different part from Windows: (Windows7 64 +

问题 I want to store a list of datetimes in a binary file in Python. EDIT: by "binary" I mean the best digital representation for each datatype. The application for this is to save GPS trackpoints composed by (unix-timestamp, latitude, longitude, elevation), so the whole structure is little-endian "Long, float, float, float", with four bytes to each value. NOTE: I don't use "unix-timestamp" due to any affection to the Unix platform, but only as an unequivocal way to represent the value of a

问题 I want to store a list of datetimes in a binary file in Python. EDIT: by "binary" I mean the best digital representation for each datatype. The application for this is to save GPS trackpoints composed by (unix-timestamp, latitude, longitude, elevation), so the whole structure is little-endian "Long, float, float, float", with four bytes to each value. NOTE: I don't use "unix-timestamp" due to any affection to the Unix platform, but only as an unequivocal way to represent the value of a

问题 I want to store a list of datetimes in a binary file in Python. EDIT: by "binary" I mean the best digital representation for each datatype. The application for this is to save GPS trackpoints composed by (unix-timestamp, latitude, longitude, elevation), so the whole structure is little-endian "Long, float, float, float", with four bytes to each value. NOTE: I don't use "unix-timestamp" due to any affection to the Unix platform, but only as an unequivocal way to represent the value of a

问题 I'm using grpc with protobuf lite in android implementation. but protobuf lite doesn't have google time stamp, and my protos has import "google/protobuf/timestamp.proto". so i added implementation 'com.google.protobuf:protobuf-java:3.7.1' to gradle that contains google time stamp. but after that code compilaition has errors. such as :Duplicate class com.google.protobuf.AbstractMessageLite found in modules protobuf-java-3.7.1.jar (com.google.protobuf:protobuf-java:3.7.1) and protobuf-lite-3.0

问题 I'm using grpc with protobuf lite in android implementation. but protobuf lite doesn't have google time stamp, and my protos has import "google/protobuf/timestamp.proto". so i added implementation 'com.google.protobuf:protobuf-java:3.7.1' to gradle that contains google time stamp. but after that code compilaition has errors. such as :Duplicate class com.google.protobuf.AbstractMessageLite found in modules protobuf-java-3.7.1.jar (com.google.protobuf:protobuf-java:3.7.1) and protobuf-lite-3.0

问题 I am working with a data frame in R labeled "mydata". The first column, labled "ts" contains unix timestamp fields. I'd like to convert these fields to days of the week. I've tried using strptime and POSIXct functions but I'm not sure how to execute them properly: > strptime(ts, "%w") --Returned this error: "Error in as.character(x) : cannot coerce type 'closure' to vector of type 'character'" I also just tried just converting it to human-readable format with POSIXct: as.Date(as.POSIXct(ts,

问题 I work with different databases in a number of different time zones (and periods of time) and one thing that normally originates problems, is the date/time definition. For this reason, and since a date is a reference to a starting value, to keep track of how it was calculated, I try to store the base date; i.e.: the minimum date supported in that particular computer/database; If I am seeing it well, this depends on the RDBMS and on the particular storage of the type. In SQL Server, I found a

问题 I have a dataframe that looks roughly like: 2020-01-01 2020-01-02 2020-01-03 2020-01-05 00:00:00 11 47 54 10 01:00:00 12 49 46 22 ... 23:00:00 15 34 22 40 Expected output... 2020-01-01 00:00:00 11 2020-01-01 01:00:00 12 ... 2020-01-01 23:00:00 12 2020-01-02 00:00:00 47 2020-01-02 01:00:00 49 ... 2020-01-01 23:00:00 34 ... 回答1: Use DataFrame.melt with convert index to column, then convert columns to datetimes and timedeltas and join together with DataFrame.pop for extract columns: df = df

问题 I have a dataframe that looks roughly like: 2020-01-01 2020-01-02 2020-01-03 2020-01-05 00:00:00 11 47 54 10 01:00:00 12 49 46 22 ... 23:00:00 15 34 22 40 Expected output... 2020-01-01 00:00:00 11 2020-01-01 01:00:00 12 ... 2020-01-01 23:00:00 12 2020-01-02 00:00:00 47 2020-01-02 01:00:00 49 ... 2020-01-01 23:00:00 34 ... 回答1: Use DataFrame.melt with convert index to column, then convert columns to datetimes and timedeltas and join together with DataFrame.pop for extract columns: df = df