c# pdf to tiff free : Create pdf signature box application Library tool html asp.net winforms online pandas179-part226

pandas: powerful Python data analysis toolkit, Release 0.18.1
dtype: int64
>>> x.searchsorted(4)
array([3])
>>> x.searchsorted([04])
array([0, 3])
>>> x.searchsorted([13], side='left')
array([0, 2])
>>> x.searchsorted([13], side='right')
array([1, 3])
>>>
>>> pd.Categorical(['apple''bread''bread''cheese''milk' ])
[apple, bread, bread, cheese, milk]
Categories (4, object): [apple < bread < cheese < milk]
>>> x.searchsorted('bread')
array([1])
# Note: an array, not a scalar
>>> x.searchsorted(['bread'])
array([1])
>>> x.searchsorted(['bread''eggs'])
array([1, 4])
>>> x.searchsorted(['bread''eggs'], side='right')
array([3, 4])
# eggs before milk
pandas.DatetimeIndex.set_names
DatetimeIndex.set_names(names, level=None, inplace=False)
Set new names on index. Defaults to returning newindex.
Parameters names : str or sequence
name(s) to set
level : int, level name, or sequence of int/level names (default None)
If the index is a MultiIndex (hierarchical), level(s) to set (None for all levels).
Otherwise level must be None
inplace : bool
if True, mutates in place
Returns new index (ofsame type and class...etc) [if inplace, returns None]
Examples
>>> Index([1234]).set_names('foo')
Int64Index([1, 2, 3, 4], dtype='int64')
>>> Index([1234]).set_names(['foo'])
Int64Index([1, 2, 3, 4], dtype='int64')
>>> idx MultiIndex.from_tuples([(1u'one'), (1u'two'),
(2, u'one'), (2, u'two')],
names=['foo', 'bar'])
>>> idx.set_names(['baz''quz'])
MultiIndex(levels=[[1, 2], [u'one', u'two']],
labels=[[0, 0, 1, 1], [0, 1, 0, 1]],
names=[u'baz', u'quz'])
>>> idx.set_names('baz', level=0)
MultiIndex(levels=[[1, 2], [u'one', u'two']],
35.10. DatetimeIndex
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VB.NET Tutorial for How to Set PDF File Access Permissions Using XDoc.PDF for .NET
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pandas: powerful Python data analysis toolkit, Release 0.18.1
labels=[[0, 0, 1, 1], [0, 1, 0, 1]],
names=[u'baz', u'bar'])
pandas.DatetimeIndex.set_value
DatetimeIndex.set_value(arr, key, value)
Fast lookup ofvalue from1-dimensional ndarray. Only use this if you know what you’re doing
pandas.DatetimeIndex.shift
DatetimeIndex.shift(n, freq=None)
Specialized shift which produces a DatetimeIndex
Parameters n : int
Periods to shift by
freq : DateOffset or timedelta-like, optional
Returns shifted : DatetimeIndex
pandas.DatetimeIndex.slice_indexer
DatetimeIndex.slice_indexer(start=None,end=None,step=None,kind=None)
Return indexer forspecified label slice. Index.slice_indexer, customized to handle time slicing.
In addition to functionality provided byIndex.slice_indexer,does the following:
•if both start and end are instances ofdatetime.time, it invokes indexer_between_time
•ifstart and end are botheitherstringorNoneperformvalue-based selection in non-monotonic cases.
pandas.DatetimeIndex.slice_locs
DatetimeIndex.slice_locs(start=None,end=None,step=None,kind=None)
Compute slice locations for input labels.
Parameters start : label, default None
If None, defaults to the beginning
end: label, default None
If None, defaults to the end
step : int,defaults None
If None, defaults to 1
kind : {‘ix’, ‘loc’,‘getitem’} or None
Returns start, end : int
pandas.DatetimeIndex.snap
DatetimeIndex.snap(freq=’S’)
Snap time stamps to nearest occurring frequency
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C# PDF Digital Signature Library: add, remove, update PDF digital
Barcode Read. Barcode Create. OCR. Twain. Edit Digital Signatures. |. Home ›› XDoc.PDF ›› C# PDF: Edit PDF Digital Signature.
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Barcode Read. Barcode Create. OCR. Twain. Edit Digital Signatures. |. Home ›› XDoc.PDF ›› VB.NET PDF: Edit PDF Digital Signature.
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pandas: powerful Python data analysis toolkit, Release 0.18.1
pandas.DatetimeIndex.sort
DatetimeIndex.sort(*args, **kwargs)
pandas.DatetimeIndex.sort_values
DatetimeIndex.sort_values(return_indexer=False,ascending=True)
Return sorted copy of Index
pandas.DatetimeIndex.sortlevel
DatetimeIndex.sortlevel(level=None, ascending=True, sort_remaining=None)
For internal compatibility with with the Index API
Sort the Index. This is for compat with MultiIndex
Parameters ascending : boolean, default True
False to sort in descending order
level, sort_remaining are compat parameters
Returns sorted_index : Index
pandas.DatetimeIndex.str
DatetimeIndex.str()
Vectorized string functions for Series and Index. NAs stay NA unless handled otherwise by a particular
method. Patterned after Python’s string methods, with some inspiration fromR’s stringrpackage.
Examples
>>> s.str.split('_')
>>> s.str.replace('_''')
pandas.DatetimeIndex.strftime
DatetimeIndex.strftime(date_format)
Return an array of formatted strings specified by date_format, which supports the same string format as
the python standard library. Details of the string format can be found inpythonstringformatdoc
Newin version 0.17.0.
Parameters date_format : str
date format string (e.g. “%Y-%m-%d”)
Returns ndarray of formatted strings
pandas.DatetimeIndex.summary
DatetimeIndex.summary(name=None)
return a summarized representation
35.10. DatetimeIndex
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Add text box to PDF file in preview. • Draw PDF markups. PDF Protection. • Sign PDF document with signature. • Erase PDF text. • Erase PDF images.
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pandas: powerful Python data analysis toolkit, Release 0.18.1
pandas.DatetimeIndex.sym_diff
DatetimeIndex.sym_diff(*args, **kwargs)
pandas.DatetimeIndex.symmetric_difference
DatetimeIndex.symmetric_difference(other, result_name=None)
Compute the sorted symmetric difference oftwo Index objects.
Parameters other : Index or array-like
result_name : str
Returns symmetric_difference : Index
Notes
symmetric_difference contains elements that appearin eitheridx1 or idx2 butnotboth. Equiv-
alent to the Index created by (idx1 - idx2) + (idx2 - idx1) with duplicates dropped.
The sortingof a resultcontaining NaN values is not guaranteed across Python versions. See GitHubissue
#6444.
Examples
>>> idx1 Index([1234])
>>> idx2 Index([2345])
>>> idx1.symmetric_difference(idx2)
Int64Index([1, 5], dtype='int64')
You can also use the ^ operator:
>>> idx1 idx2
Int64Index([1, 5], dtype='int64')
pandas.DatetimeIndex.take
DatetimeIndex.take(indices, axis=0, allow_fill=True, fill_value=None, **kwargs)
return a new %(klass)s of the values selected by the indices
For internal compatibility with numpy arrays.
Parameters indices : list
Indices to be taken
axis : int,optional
The axis overwhich to select values, always 0.
allow_fill : bool,default True
fill_value : bool,default None
If allow_fill=True and fill_value is not None, indices specified by -1 is regarded
as NA. If Index doesn’t holdNA, raise ValueError
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Chapter 35. API Reference
How to C#: Basic SDK Concept of XDoc.PDF for .NET
create, load, combine, and split PDF file(s), and add, create, insert, delete, re To be specific, you can edit PDF password and digital signature, and set
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VB.NET PDF: Basic SDK Concept of XDoc.PDF
create, load, combine, and split PDF file(s), and add, create, insert, delete, re To be specific, you can edit PDF password and digital signature, and set
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pandas: powerful Python data analysis toolkit, Release 0.18.1
See also:
numpy.ndarray.take
pandas.DatetimeIndex.to_datetime
DatetimeIndex.to_datetime(dayfirst=False)
pandas.DatetimeIndex.to_julian_date
DatetimeIndex.to_julian_date()
Convert DatetimeIndex to Float64Index of Julian Dates. 0 Julian date is noon January 1, 4713 BC.
http://en.wikipedia.org/wiki/Julian_day
pandas.DatetimeIndex.to_native_types
DatetimeIndex.to_native_types(slicer=None,**kwargs)
slice and dice then format
pandas.DatetimeIndex.to_period
DatetimeIndex.to_period(freq=None)
Cast to PeriodIndex at a particularfrequency
pandas.DatetimeIndex.to_perioddelta
DatetimeIndex.to_perioddelta(freq)
Calcuates TimedeltaIndexofdifference between indexvalues and index converted to PeriodIndexat spec-
ified freq. Used for vectorized offsets
Newin version 0.17.0.
Parameters freq: Period frequency
Returns y : TimedeltaIndex
pandas.DatetimeIndex.to_pydatetime
DatetimeIndex.to_pydatetime()
Return DatetimeIndex as object ndarray ofdatetime.datetime objects
Returns datetimes : ndarray
pandas.DatetimeIndex.to_series
DatetimeIndex.to_series(keep_tz=False)
Create aSeries withbothindexandvaluesequaltothe indexkeys useful withmap forreturningan indexer
based on an index
Parameters keep_tz : optional, defaults False.
35.10. DatetimeIndex
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Password, digital signature and PDF text, image and page added to a specific location on PDF file page. In addition, you can easily create, modify, and delete
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pandas: powerful Python data analysis toolkit, Release 0.18.1
return the data keeping the timezone.
If keep_tz is True:
If the timezone is not set, the resulting Series will have a datetime64[ns]
dtype.
Otherwise the Series will have an datetime64[ns, tz] dtype; the tz will be
preserved.
If keep_tz is False:
Series will have a datetime64[ns] dtype. TZ aware objects will have the tz
removed.
Returns Series
pandas.DatetimeIndex.tolist
DatetimeIndex.tolist()
return a list of the underlying data
pandas.DatetimeIndex.transpose
DatetimeIndex.transpose(*args, **kwargs)
return the transpose, which is by definition self
pandas.DatetimeIndex.tz_convert
DatetimeIndex.tz_convert(tz)
Convert tz-aware DatetimeIndex from one time zone to another(using pytz/dateutil)
Parameters tz : string,pytz.timezone, dateutil.tz.tzfile or None
Time zone fortime. Corresponding timestamps would be converted to time zone
ofthe TimeSeries. None will remove timezone holding UTC time.
Returns normalized: DatetimeIndex
Raises TypeError
If DatetimeIndex is tz-naive.
pandas.DatetimeIndex.tz_localize
DatetimeIndex.tz_localize(*args, **kwargs)
Localize tz-naive DatetimeIndex to given time zone (using pytz/dateutil), or remove timezone from tz-
aware DatetimeIndex
Parameters tz : string,pytz.timezone, dateutil.tz.tzfile or None
Time zone fortime. Corresponding timestamps would be converted to time zone
ofthe TimeSeries. None will remove timezone holding local time.
ambiguous : ‘infer’,bool-ndarray, ‘NaT’, default ‘raise’
• ‘infer’will attempt to infer fall dst-transition hours based on order
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pandas: powerful Python data analysis toolkit, Release 0.18.1
• bool-ndarray where True signifies a DST time, False signifies a non-DST time (note
that this flag is only applicable for ambiguous times)
• ‘NaT’ will return NaT where there are ambiguous times
• ‘raise’will raise an AmbiguousTimeErrorif there are ambiguous times
infer_dst : boolean,default False (DEPRECATED)
Attempt to infer fall dst-transition hours based on order
Returns localized : DatetimeIndex
Raises TypeError
If the DatetimeIndex is tz-aware and tz is not None.
pandas.DatetimeIndex.union
DatetimeIndex.union(other)
Specialized union for DatetimeIndex objects. If combine overlapping ranges with the same DateOffset,
will be much faster than Index.union
Parameters other : DatetimeIndex or array-like
Returns y : Index orDatetimeIndex
pandas.DatetimeIndex.union_many
DatetimeIndex.union_many(others)
Abit of a hack to accelerate unioning a collection of indexes
pandas.DatetimeIndex.unique
DatetimeIndex.unique()
Index.unique with handling for DatetimeIndex/PeriodIndex metadata
Returns result: DatetimeIndex or PeriodIndex
pandas.DatetimeIndex.value_counts
DatetimeIndex.value_counts(normalize=False, sort=True, ascending=False, bins=None,
dropna=True)
Returns object containing counts of unique values.
The resulting object will be in descending order so that the first element is the most frequently-occurring
element. Excludes NA values bydefault.
Parameters normalize : boolean,default False
If True then the objectreturned willcontain the relative frequencies of the unique
values.
sort : boolean,default True
Sort by values
ascending : boolean,default False
Sort in ascending order
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bins : integer, optional
Rather than count values, group them into half-open bins, a convenience for
pd.cut, onlyworks with numeric data
dropna : boolean,default True
Don’t include counts of NaN.
Returns counts : Series
pandas.DatetimeIndex.view
DatetimeIndex.view(cls=None)
35.10.2 Time/Date Components
DatetimeIndex.year
The yearof the datetime
DatetimeIndex.month
The month as January=1, December=12
DatetimeIndex.day
The days of the datetime
DatetimeIndex.hour
The hours ofthe datetime
DatetimeIndex.minute
The minutes of the datetime
DatetimeIndex.second
The seconds of the datetime
DatetimeIndex.microsecond
The microseconds of the datetime
DatetimeIndex.nanosecond
The nanoseconds of the datetime
DatetimeIndex.date
Returns numpy array of datetime.date.
DatetimeIndex.time
Returns numpy array of datetime.time.
DatetimeIndex.dayofyear
The ordinal day of the year
DatetimeIndex.weekofyear
The week ordinal of the year
DatetimeIndex.week
The week ordinal of the year
DatetimeIndex.dayofweek
The day of the week with Monday=0, Sunday=6
DatetimeIndex.weekday
The day of the week with Monday=0, Sunday=6
DatetimeIndex.weekday_name
The name of day in a week (ex: Friday)
DatetimeIndex.quarter
The quarter ofthe date
DatetimeIndex.tz
DatetimeIndex.freq
get/set the frequncy ofthe Index
DatetimeIndex.freqstr
Return the frequency object as a string if its set, otherwise None
DatetimeIndex.is_month_start
Logical indicating if first dayof month (defined by frequency)
DatetimeIndex.is_month_end
Logical indicating if last day of month (defined by frequency)
DatetimeIndex.is_quarter_start
Logical indicating if first dayof quarter (defined by frequency)
DatetimeIndex.is_quarter_end
Logical indicating if last day of quarter (defined by frequency)
DatetimeIndex.is_year_start
Logical indicating if first dayof year (defined byfrequency)
DatetimeIndex.is_year_end
Logical indicating if last day of year (defined by frequency)
DatetimeIndex.inferred_freq
pandas.DatetimeIndex.year
DatetimeIndex.year
The yearof the datetime
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pandas.DatetimeIndex.month
DatetimeIndex.month
The month as January=1, December=12
pandas.DatetimeIndex.day
DatetimeIndex.day
The days of the datetime
pandas.DatetimeIndex.hour
DatetimeIndex.hour
The hours ofthe datetime
pandas.DatetimeIndex.minute
DatetimeIndex.minute
The minutes of the datetime
pandas.DatetimeIndex.second
DatetimeIndex.second
The seconds of the datetime
pandas.DatetimeIndex.microsecond
DatetimeIndex.microsecond
The microseconds of the datetime
pandas.DatetimeIndex.nanosecond
DatetimeIndex.nanosecond
The nanoseconds of the datetime
pandas.DatetimeIndex.date
DatetimeIndex.date
Returns numpy array of datetime.date. The date part ofthe Timestamps.
pandas.DatetimeIndex.time
DatetimeIndex.time
Returns numpy array of datetime.time. The time part ofthe Timestamps.
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pandas: powerful Python data analysis toolkit, Release 0.18.1
pandas.DatetimeIndex.dayofyear
DatetimeIndex.dayofyear
The ordinal day of the year
pandas.DatetimeIndex.weekofyear
DatetimeIndex.weekofyear
The week ordinal of the year
pandas.DatetimeIndex.week
DatetimeIndex.week
The week ordinal of the year
pandas.DatetimeIndex.dayofweek
DatetimeIndex.dayofweek
The day of the week with Monday=0, Sunday=6
pandas.DatetimeIndex.weekday
DatetimeIndex.weekday
The day of the week with Monday=0, Sunday=6
pandas.DatetimeIndex.weekday_name
DatetimeIndex.weekday_name
The name of day in a week (ex: Friday)
New in version 0.18.1.
pandas.DatetimeIndex.quarter
DatetimeIndex.quarter
The quarter of the date
pandas.DatetimeIndex.tz
DatetimeIndex.tz = None
pandas.DatetimeIndex.freq
DatetimeIndex.freq
get/set the frequncy ofthe Index
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