Convert String Date to String date different format
SimpleDateFormat format1 = new SimpleDateFormat("yyyy-MM-dd");
SimpleDateFormat format2 = new SimpleDateFormat("dd-MM-yyyy");
Date date = format1.parse("2013-02-21");
System.out.println(format2.format(date));
How to convert a date string to different format
I assume I have import datetime
before running each of the lines of code below
datetime.datetime.strptime("2013-1-25", '%Y-%m-%d').strftime('%m/%d/%y')
prints "01/25/13"
.
If you can't live with the leading zero, try this:
dt = datetime.datetime.strptime("2013-1-25", '%Y-%m-%d')
print '{0}/{1}/{2:02}'.format(dt.month, dt.day, dt.year % 100)
This prints "1/25/13"
.
EDIT: This may not work on every platform:
datetime.datetime.strptime("2013-1-25", '%Y-%m-%d').strftime('%m/%d/%y')
Convert Date String to another Date string with different format
What you are doing is fine.
Probably you can improve it by using DateTime.TryParseExact
and on successful parsing, format the DateTime
object in other format.
string dateString = "20130916";
DateTime parsedDateTime;
string formattedDate;
if(DateTime.TryParseExact(dateString, "yyyyMMdd",
CultureInfo.InvariantCulture,
DateTimeStyles.None,
out parsedDateTime))
{
formattedDate = parsedDateTime.ToString("MM/dd/yyyy");
}
else
{
Console.WriteLine("Parsing failed");
}
Formatting a String date into a different format in Java
Use this code to format your `2017-05-23T06:25:50'
String strDate = "2017-05-23T06:25:50";
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss");
Date convertedDate = new Date();
try {
convertedDate = dateFormat.parse(strDate);
SimpleDateFormat sdfnewformat = new SimpleDateFormat("MMM dd yyyy");
String finalDateString = sdfnewformat.format(convertedDate);
} catch (ParseException e) {
e.printStackTrace();
}
The converted finalDateString
set to your textView
swift - Convert a String to a Date and then to a String in a different format
Updated for Swift 3.0
You need two date formatters - one to make sense of your input string and convert to a NSDate, and a different formatter to create the output string
let myDateString = "2016-01-01 04:31:32.0"
let dateFormatter = DateFormatter()
dateFormatter.dateFormat = "yyyy-MM-dd HH:mm:ss.A"
let myDate = dateFormatter.date(from: myDateString)!
dateFormatter.dateFormat = "MMM dd, YYYY"
let somedateString = dateFormatter.string(from: myDate)
I have updated this answer to change the date formatter from YYYY to yyyy. In most cases, there will be no difference between the two, but YYYY may treat the first few days of the year as being part of the last complete week of the previous year.
The Apple developer guides explain it like this.
A common mistake is to use YYYY. yyyy specifies the calendar year whereas YYYY specifies the year (of “Week of Year”), used in the ISO year-week calendar. In most cases, yyyy and YYYY yield the same number, however they may be different. Typically you should use the calendar year.
Convert string of date format to string of another date format
try this
public string ConvertStringDateFormat(string date, string convertToDateFormat)
{
return Convert.ToString(Convert.ToDateTime(date),convertToDateFormat);
}
Converting date-string to a different format
Use java.util.DateFormat
:
DateFormat fromFormat = new SimpleDateFormat("yyyy-MM-dd");
fromFormat.setLenient(false);
DateFormat toFormat = new SimpleDateFormat("dd-MM-yyyy");
toFormat.setLenient(false);
String dateStr = "2011-07-09";
Date date = fromFormat.parse(dateStr);
System.out.println(toFormat.format(date));
Parse String to Date with Different Format in Java
Take a look at SimpleDateFormat
. The code goes something like this:
SimpleDateFormat fromUser = new SimpleDateFormat("dd/MM/yyyy");
SimpleDateFormat myFormat = new SimpleDateFormat("yyyy-MM-dd");
try {
String reformattedStr = myFormat.format(fromUser.parse(inputString));
} catch (ParseException e) {
e.printStackTrace();
}
Convert string date to a different format in pandas dataframe
If you convert the column of strings to a time series, you could use the dt.strftime
method:
import numpy as np
import pandas as pd
nan = np.nan
df = pd.DataFrame({'TBD': [nan, nan, nan], 'TBD.1': [nan, nan, nan], 'TBD.2': [nan, nan, nan], 'TimeStamp': ['2016/06/08 17:19:53', '2016/06/08 17:19:54', '2016/06/08 17:19:54'], 'Value': [0.062941999999999998, 0.062941999999999998, 0.062941999999999998]})
df['TimeStamp'] = pd.to_datetime(df['TimeStamp']).dt.strftime('%m/%d/%Y %H:%M:%S')
print(df)
yields
TBD TBD.1 TBD.2 TimeStamp Value
0 NaN NaN NaN 06/08/2016 17:19:53 0.062942
1 NaN NaN NaN 06/08/2016 17:19:54 0.062942
2 NaN NaN NaN 06/08/2016 17:19:54 0.062942
Since you want to convert a column of strings to another (different) column of strings, you could also use the vectorized str.replace
method:
import numpy as np
import pandas as pd
nan = np.nan
df = pd.DataFrame({'TBD': [nan, nan, nan], 'TBD.1': [nan, nan, nan], 'TBD.2': [nan, nan, nan], 'TimeStamp': ['2016/06/08 17:19:53', '2016/06/08 17:19:54', '2016/06/08 17:19:54'], 'Value': [0.062941999999999998, 0.062941999999999998, 0.062941999999999998]})
df['TimeStamp'] = df['TimeStamp'].str.replace(r'(\d+)/(\d+)/(\d+)(.*)', r'\2/\3/\1\4')
print(df)
since
In [32]: df['TimeStamp'].str.replace(r'(\d+)/(\d+)/(\d+)(.*)', r'\2/\3/\1\4')
Out[32]:
0 06/08/2016 17:19:53
1 06/08/2016 17:19:54
2 06/08/2016 17:19:54
Name: TimeStamp, dtype: object
This uses regex to rearrange pieces of the string without first parsing the
string as a date. This is faster than the first method (mainly because it skips
the parsing step), but it also has the disadvantage of not checking that the
date strings are valid dates.
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