Framework for data processing and data preparation DAG (directed acyclic graph) pipelines.
Base class for data-pipe errors.
Invalid parameter passed.
Returns offending parameter name.
Returns offending parameter value.
Indicates a pipeline terminated with no result.
Decorator signifying a (generator) function is a filter function.
Example:
>>> # Function adding 1 to anything (there are simpler ways of doing this):
>>> def add_1():
... @filters
... def _act(target):
... try:
... while True:
... target.send((yield) + 1)
... except GeneratorExit:
... target.close()
... return _act
Examples:
>>> # Print the smallest value in three files
>>> a = freeze(min_())
>>> for f_name in ['data1.txt', 'data2.txt', 'data3.txt']:
... read_lines(f_name) | cast(double) | a
>>> print thaw(a)
>>> # Calculate the mean and standard deviation of the elements in lists
>>> # which are longer than 100.
>>> a = freeze(mean() + stddev())
>>> for l in lists:
... if len(l) > 100:
... source(l) | a
>>> mean, stddev = thaw(a)
Decorator signifying a (generator) function is a sink function.
Example:
>>> # Function returning the sum of the first two values sent to it:
... def add_1():
... @filters
... def _act(target):
... i, sum = 0, 0
... try:
... while True:
... if i < 2:
... sum += (yield)
... i += 1
... except GeneratorExit:
... if i >= 2:
... target.send(sum)
... target.close()
... return _act
Creates a source from any iterable sequence.
Examples:
>>> source([1, 2, 3, 4]) | count()
4
>>> source(()) | count()
0
Decorator signifying a (generator) function is a source function.
Example:
>>> # Function returning 10 '1's (there are simpler ways of doing this):
>>> def ten_ones():
... @sources
... def _act():
... for i in xrange(10):
... yield '1'
... return _act
Example:
>>> def some_implementation(target):
... pipe = filt(lambda x : 2 * x)
... sub_target = sub_pipe_target(pipe, target)
... try:
... while True:
... sub_target.send((yield))
... except GeneratorExit:
... sub_target.close()
... target.close()
Examples:
>>> # Print the smallest value in three files
>>> a = freeze(min_())
>>> for f_name in ['data1.txt', 'data2.txt', 'data3.txt']:
... read_lines(f_name) | cast(double) | a
>>> print thaw(a)
>>> # Calculate the mean and standard deviation of the elements in lists
>>> # which are longer than 100.
>>> a = freeze(mean() + stddev())
>>> for l in lists:
... if len(l) > 100:
... source(l) | a
>>> mean, stddev = thaw(a)
Base class for data-pipe errors.
Indicates a name was not found in a CSV header.
Returns problematic name.
Recursively iterate through files.
Keyword Arguments: directory – Directory to perform the search (default ‘.’)
Example:
>>> # Creates a list of files in the current directory.
>>> os_walk() | to_list()
See the online documentation for an example.
Creates a source from any iterable sequence.
Examples:
>>> source([1, 2, 3, 4]) | count()
4
>>> source(()) | count()
0
Decorator signifying a (generator) function is a source function.
Example:
>>> # Function returning 10 '1's (there are simpler ways of doing this):
>>> def ten_ones():
... @sources
... def _act():
... for i in xrange(10):
... yield '1'
... return _act
Streams the lines from some stream.
Examples:
>>> # Places a file's lines in a list.
>>> stream_lines('data.csv') | to_list()
Streams delimited (e.g., by commas for CSV files, or by tabs for TAB files) values as tuples.
delimit – Delimiting binary character (default b’,’). comment – Comment-starting binary character (default b’#”). Any character starting from this
one until the line end will be ignored.
skip_init_space – Whether spaces starting a field will be ignored (default True).
Examples:
>>> # Find the correlation between two named columns.
>>> csv_vals('meteo.csv', ('wind', 'rain')) | corr()
0.74
>>> # Find the correlation between two indexed columns.
>>> csv_vals('data.csv', (0, 3)) | corr()
0.23
Appends to the end of all elements.
Example:
>>> source([1, 2, 3, 4]) | append(5) | to_list()
[1, 2, 3, 4, 5]
Returns a cast of elements.
Examples:
>>> source(['1']) | cast(float) | to_list()
[1]
>>> source([('1', '2')]) | cast((int, float)) | to_list()
[1, 2.0]
Splits the values in a delimited stream (e.g., by commas for CSV files, or by tabs for TAB files) as tuples.
delimit – Delimiting binary character (default b’,’). comment – Comment-starting binary character (default b’#”). Any character starting from this
one until the line end will be ignored.
skip_init_space – Whether spaces starting a field will be ignored (default True).
Examples:
>>> # Assume the file 'junky.txt' contains lines, those containing the string
>>> # 'moshe' are split by tabs, and we wish to find the correlation between the
>>> 2nd and 5th values in these lines.
>>> stream_lines('junky.txt') | grep('moshe') | csv_split( (2, 5) ) | corr()
0.23
Transforms a sequence into a cumulative moving average of it.
Examples:
>>> source([1., 2., 3., 4.]) | cum_ave(0) | to_list()
[1., 1.5, 2, 2.5]
Transforms a sequence into an exponential moving average of it.
Arguments: alpha – Responsiveness factor, should be between 0 and 1.
Example:
>>> source([1., 2., 3., 4.]) | exp_ave(0.75) | to_list()
[1., 1.75, 2.6875, 3.671875]
Filters filenames - checks if they pass some criteria.
Example:
>>> # Counts the number of files of the form 'data?.csv'
>>> print os_walk() | filename_filt('data?.csv') | count()
Filter (transform elements and / or suppress them).
Keyword Arguments: trans – Transformation function for each element (default None). pre – Suppression function checked against each element before
transformation function, if any (default None).
Example:
>>> # square-root of non-negative elements
>>> filter(trans = lambda x : math.sqrt(x), pre = lambda x : x >= 0)
Decorator signifying a (generator) function is a filter function.
Example:
>>> # Function adding 1 to anything (there are simpler ways of doing this):
>>> def add_1():
... @filters
... def _act(target):
... try:
... while True:
... target.send((yield) + 1)
... except GeneratorExit:
... target.close()
... return _act
Filters strings based on the occurrence of a substring or a regular expression.
Examples:
>>> source(['aa', 'aab', 'b']) | grep('b') | to_list()
['aab', 'b']
>>> source(['aa', 'aab', 'b']) | grep(re.compile(r'(a+)b')) | to_list()
['aab']
Prepends to the start of all elements.
Example:
>>> source([1, 2, 3, 4]) | prepend(0) | to_list()
[0, 1, 2, 3, 4]
Randomly passes some of the elements, with a given probability.
Example:
>>> n = 9999
>>> print (source(xrange(n)) | rand_prob_sample(0.7) | count()) / float(n)
0.702870287029
Sends on whatever is passed to it.
Example:
>>> # Find the rain auto-correlation relative to the signal 5 time units in the future.
>>> csv_vals(open('meteo.csv'), 'rain') | relay() + skip(5) | corr()
Returns a selection of the selected indices of indexable elements.
Arguments: inds – either an integer, or an iterable of integers.
Examples:
>>> source([(1, 2, 3), (4, 5, 6)]) | select_inds(2) | to_list()
[3, 6]
>>> source([(1, 2, 3), (4, 5, 6)]) | select_inds((0, 2)) | to_list()
[(1, 3), (4, 6)]
>>> source([(1, 2, 3), (4, 5, 6)]) | select_inds(()) | to_list()
[(), ()]
Skips n elements.
Arguments: n - If a positive integer, skips n elements from start, else
skips n element from the end
Example:
>>> source([1, 2, 3, 4]) | skip(2) | to_list()
[3, 4]
>>> source([1, 2, 3, 4]) | skip(-2) | to_list()
[1, 2]
Example:
>>> source(['a,b', 'c,d,e']) | split() | to_list()
[('a', 'b'), ('c', 'd', 'e')]
Traces elements to a stream. Useful for debugging problematic streams.
Example:
>>> source([1, 2, 3, 'd']) | trace() | sum()
0 : 1
1 : 2
2 : 3
3 : d
Examples:
>>> source([1, 2, 3, 4, 1, 0, 4, 4]) | window_max(2) | to_list()
[1, 2, 3, 4, 4, 1, 4, 4]
Transforms a sequence into its minimum within some window. Uses an algorithm from http://home.tiac.net/~cri/2001/slidingmin.html
Arguments: wnd_len – Averaging window length.
Keyword Arguments: cmp_ – Comparison function (default: cmp) used for deciding which is smaller than which.
Examples:
>>> source([1, 2, 3, 4, 1, 0, 4, 4]) | window_min(2) | to_list()
[1, 1, 2, 3, 1, 0, 0, 4]
Transforms a sequence into its quantiles within some window.
Examples:
>>> source([1, 4, 2, 4, 6, 9, 2, 4, 5]) | window_quantile(2, 0.5) | to_list()
[1, 4, 4, 4, 6, 9, 9, 4, 5]
>>> source([1, 4, 2, 4, 6, 9, 2, 4, 5]) | window_quantile(3, 0.5) | to_list()
[1, 4, 2, 4, 4, 6, 6, 4, 4]
Examples:
>>> source([1., 2., 3., 4.]) | window_simple_ave(0) | to_list()
[1., 1.5, 2.5, 3.5]
Calculates the Pearson correlation coefficient between tuples.
Examples: >>> source([1, 2, 3, 4]) + source([1, 2, 3, 4]) | corr() 1
>>> source([(60, 3.1), (61, 3.6), (62, 3.8), (63, 4), (65, 4.1)]) | corr()
0.9119
Computes the number of piped elements.
Example:
>>> source([1, 2, 3, 4]) | count()
4
Computes the largest element.
Example:
>>> source([1, 2, 3, 4]) | max_()
4
Calculates the mean of all elements.
Example:
>>> source([2, 4, 4, 4, 5, 5, 7, 9]) | mean()
5
Computes the smallest element.
Example: >>> source([1, 2, 3, 4]) | min_() 1
Returns the n-th piped element.
Example:
>>> source([1, 2, 3, 4]) | nth(0)
1
>>> source([1, 2, 3, 4]) | nth(-1)
4
General purpose sink.
Examples:
>>> source([1, 2, 3]) | sink(lambda x : x ** 2)
9
>>> source([1, 2]) | sink('hello')
'hello'
>>> source([1, 2, 3]) | sink('hello')
'hello'
Decorator signifying a (generator) function is a sink function.
Example:
>>> # Function returning the sum of the first two values sent to it:
... def add_1():
... @filters
... def _act(target):
... i, sum = 0, 0
... try:
... while True:
... if i < 2:
... sum += (yield)
... i += 1
... except GeneratorExit:
... if i >= 2:
... target.send(sum)
... target.close()
... return _act
Example:
>>> source(xrange(100)) | rand_size_sample(2)
>>> [34, 12]
Calculates the sample standard deviation.
Example:
>>> source([2, 4, 4, 4, 5, 5, 7, 9]) | stddev(0)
2
Computes the sum of piped elements.
Example:
>>> source([1, 2, 3, 4]) | sum_()
10
Converts all elements to a dictionary. Given tuples, the first entry of each is the key, and the second is the data.
Example:
>>> source(((1, 'a'), (2, 'b'), (3, 'b'), (4, 'j'))) | to_dict()
{1: 'a', 2: 'b', 3: 'b', 4: 'j'}
Converts all elements to a list.
Example:
>>> source((1, 2, 3, 4)) | to_list()
[1, 2, 3, 4]
is a tuple, its sub-elements will be separated by the delimit byte. Elements will be separated by the line-terminator byte.
delimit – Delimiting binary character between elements (default b’,’). line_terminator – Between-element binary character element (default b’
‘)
- See Also:
- np.chunks_to_stream
Examples:
>>> # Writes a CSV file of 3 lines, each containing 2 sub-elements >>> source([(1, 2), (3, 4), (5, 6)] | to_stream('data.csv') 3>>> # Same but with headings >>> source([(1, 2), (3, 4), (5, 6)] | to_stream('data.csv', names = ('wind', 'rain')) 3>>> # Same but with tab separators. >>> source([(1, 2), (3, 4), (5, 6)] | to_stream('data.csv', names = ('wind', 'rain'), delimit = b' ') 3
Chains the result of applying an ad-hoc created pipe to each element.
Example:
>>> # Chain each element twice.
>>> source([1, 2, 3]) | ... chain(lambda p : source([p] * 2])) | ... to_list()
[1, 1, 2, 2, 3, 3]
key_pipe – Function mapping each key to a pipe.
Example:
>>> # Count number of tuples with same first item.
>>> source([(1, 1), (1, 455), (13, 0)]) | \
... consec_group(
... lambda p : p[0],
... lambda k : sink(k) + count()) | \
... to_list()
[(1, 2), (13, 1)]
Performs an SQL-style join with a dictionary.
joined – Dictionary of items with which to join. key – Function mapping each element to a key. This key will
be used to decide with which joined element (if any) to join.
Examples:
>>> # Assume employee.csv has the following content:
>>> # Name,EmpId,DeptName
>>> # Harry,3415,Finance
>>> # Sally,2241,Sales
>>> # George,3401,Finance
>>> # Harriet,2202,Sales
>>> # Nelson,2455,Entertainment
>>> #
>>> # Assume dept.csv has the following content:
>>> # DeptName,Manager
>>> # Finance,George
>>> # Sales,Harriet
>>> # Production,Charles
>>> # Create a dictionary mapping employees to managers:
>>> d = csv_vals('data/employee.csv', ('Name', 'EmpId', 'DeptName'), (str, int, str)) | ... dict_join(
... csv_vals('data/dept.csv', ('DeptName', 'Manager'), (str, str)) | to_dict(),
... lambda name_id_dept : name_id_dept[2],
... lambda dept, manager : filt(lambda name_id_dept : (name_id_dept[0], manager)),
... filt(lambda name_id_dept : (name_id_dept[0], None)),
... None) | ... to_dict()
>>> assert d['Harriet'] == 'Harriet'
>>> assert d['Nelson'] is None
>>> # Create a dictionary mapping managers to the number of people they manage:
>>> d = csv_vals('data/employee.csv', ('Name', 'EmpId', 'DeptName'), (str, int, str)) | ... dict_join(
... csv_vals('data/dept.csv', ('DeptName', 'Manager'), (str, str)) | to_dict(),
... lambda name_id_dept : name_id_dept[2],
... lambda dept, manager : sink(manager) + count(),
... None,
... filt(lambda dept_manager : (dept_manager[1], 0))) | ... to_dict()
>>> assert d['Harriet'] == 2
>>> assert d['Charles'] == 0
Filter (transform elements and / or suppress them).
Keyword Arguments: trans – Transformation function for each element (default None). pre – Suppression function checked against each element before
transformation function, if any (default None).
Example:
>>> # square-root of non-negative elements
>>> filter(trans = lambda x : math.sqrt(x), pre = lambda x : x >= 0)
Decorator signifying a (generator) function is a filter function.
Example:
>>> # Function adding 1 to anything (there are simpler ways of doing this):
>>> def add_1():
... @filters
... def _act(target):
... try:
... while True:
... target.send((yield) + 1)
... except GeneratorExit:
... target.close()
... return _act
key_pipe – Function mapping each key to a pipe.
Example:
>>> # Count number of tuples with same first item.
>>> source([(1, 1), (13, 0), (1, 455)]) | \
... consec_group(
... lambda p : p[0],
... lambda k : sink(k) + count()) | \
... to_list()
[(1, 2), (13, 1)]
Example:
>>> def some_implementation(target):
... pipe = filt(lambda x : 2 * x)
... sub_target = sub_pipe_target(pipe, target)
... try:
... while True:
... sub_target.send((yield))
... except GeneratorExit:
... sub_target.close()
... target.close()
Converts all elements to a list.
Example:
>>> source((1, 2, 3, 4)) | to_list()
[1, 2, 3, 4]
Numpy stages.
Example:
>>> # Reads from a binary file, and writes the cumulative average to a different one.
>>> np.chunk_stream_bytes('foo.dat') | np.cum_ave() | np.chunks_to_stream_bytes('wind_ave.dat')
stream – Either the name of a file or a binary stream. cols – Indication of which columns to read. If either an integer or a tuple of integers,
the corresponding columns will be read. If either a string or a tuple of strings, the columns whose first rows have these string names (excluding the first row) will be read.
delimit – Delimiting binary character (default b’,’). comment – Comment-starting binary character (default b’#”). Any character starting from this
one until the line end will be ignored.
skip_init_space – Whether spaces starting a field will be ignored (default True). max_elems – Number of rows per chunk (last might have less) (default 8192).
Examples:
>>> # Find the correlation between two named columns.
>>> np.chunk_stream_vals('meteo.csv', ('day', 'wind'), (float, float), (0, 0)) | np.corr()
0.74
>>> #Equivalent to:
>>> np.chunk_stream_vals('meteo.csv', ('day', 'wind')) | np.corr()
0.74
>>> # Find the correlation between two indexed columns.
>>> np.chunk_stream_vals('meteo.csv', (3, 0) | np.corr()
0.23
Transforms a sequence of elements into chunks.
Example:
>>> some_strange_source() | np.chunk() | np.min_()
0.000000133
Example:
>>> # Reads from a CSV file, and writes the cumulative average to a different one.
>>> np.chunk_stream_vals('meteo.csv', 'wind') | np.cum_ave() | np.chunks_to_stream('wind_ave.csv', 'wind')
Example:
>>> # Reads from a CSV file, and writes the exponential average to a different one.
>>> np.chunk_stream_vals('meteo.csv', 'wind') | np.cum_ave() | np.chunks_to_stream('wind_ave.csv', 'wind')
Skips the first n elements (not chunks) from a stream of chunks.
Example:
>>> # Calculate the mean of 'wind' column elements except the first three.
>>> np.chunk_stream_vals('meteo.csv', 'wind') | np.skip(n) | np.mean()
34.2
Complementary action to chunk. Transforms the rows of an array to tuples.
Example:
>>> l = source([numpy.array([[1, 2], [3, 4]])]) | np.unchunk() | to_list()
>>> assert l[0] == (1, 2)
Finds means chunks. They must have the same size.
Example:
>>> source([numpy.array([1, 2, 3, 4]), numpy.array([5, 6, 7, 8])]) | np.chunks_mean()
array([3, 4, 5, 6])
Calculates the sample standard deviation of chunks. They must have the same size. See the documentation of stddev in the parent module.
Example:
>>> source([numpy.array([1, 2, 3, 4]), numpy.array([5, 6, 7, 8])]) | np.chunks_stddev()
Tmp Ami Complete
Sums chunks. They must have the same size.
Example:
>>> source([numpy.array([1, 2, 3, 4]), numpy.array([5, 6, 7, 8])]) | np.chunks_sum()
array([6, 8, 10, 12])
is a tuple, its sub-elements will be separated by the delimit byte. Elements will be separated by the line-terminator byte.
fmt – See corresponding parameter in numpy.savetxt delimit – Delimiting binary character between elements (default b’,’). line_terminator – Between-element binary character element (default b’
‘)
- See Also:
- to_stream
Examples:
>>> # Reads from a CSV file, and writes the cumulative average to a different one. >>> np.chunk_stream_vals('meteo.csv', 'wind') | np.cum_ave() | np.chunks_to_stream('wind_ave.csv', 'wind')
Writes chunks to a binary stream.
Example:
>>> # Reads from a binary file, and writes the cumulative average to a different one.
>>> np.chunk_stream_bytes('foo.dat') | np.cum_ave() | np.chunks_to_stream_bytes('wind_ave.dat')
Concatenates chunks.
Example:
>>> assert numpy.allclose(source(xrange(30000)) | np.chunk() | concatenate_chunks(), array(xrange(30000)))
Finds the correlation between streams of chunk-pairs, or between streams of 2-column chunks.
Examples:
>>> # Find the correlation between two indexed columns.
>>> np.chunk_stream_vals('meteo.csv', (3, 0) | np.corr()
0.23
Computes the number of piped chunks’ elements.
Examples:
>>> chunk_stream_bytes('meteo.dat') | np.count()
355544
>>> source([1, 2, 3, 4]) | np.chunk() | np.count()
4
>>> source([(1, 2), (3, 4)]) | np.chunk() | np.count()
2
Computes the maximum of piped chunks’ elements.
Examples:
>>> chunk_stream_bytes('meteo.dat') | np.max_()
12344.32
>>> source([1, 2, 3, 4]) | np.chunk() | np.max_()
1
>>> source([(1, 2), (3, 4)]) | np.chunk() | np.max_()
1
>>> source([(1, 2), (3, 4)]) | np.chunk() | np.max_(axis = 0)
[1, 2]
Computes the mean of piped chunks’ elements.
Examples:
>>> chunk_stream_bytes('meteo.dat') | mean_()
23.2
>>> source([1, 2, 3, 4]) | np.chunk() | np.mean()
2.5
>>> source([(1, 2), (3, 4)]) | np.chunk() | np.mean()
2.5
>>> source([(1, 2), (3, 4)]) | np.chunk() | np.mean(axis = 0)
[2, 3]
Computes the minimum of piped chunks’ elements.
Examples:
>>> chunk_stream_bytes('meteo.dat') | np.min_()
12.32
>>> source([1, 2, 3, 4]) | np.chunk() | np.min_()
1
>>> source([(1, 2), (3, 4)]) | np.chunk() | np.min_()
1
>>> source([(1, 2), (3, 4)]) | np.chunk() | np.min_(axis = 0)
[1, 2]
Computes the sum of piped chunks’ elements.
Examples:
>>> chunk_stream_bytes('meteo.dat') | sum_()
9877544
>>> source([1, 2, 3, 4]) | np.chunk() | np.sum_()
10
>>> source([(1, 2), (3, 4)]) | np.chunk() | np.sum_()
10
>>> source([(1, 2), (3, 4)]) | np.chunk() | np.sum_(axis = 0)
[4, 6]
Converts all elements to a numpy.array.
Keyword Arguments: dtype – Same as in the ctor of numpy.array (default None).
Examples:
>>> source(((1, 2), (3, 4))) | to_array()
array([[1, 2],
... [3, 4]])+
>>> a = source([1, 2, 3, 4]) | to_array(dtype = numpy.float6464)
Stacks chunks vertically. They must have the same size.
Example:
>>> source([numpy.array([1, 2, 3, 4]), numpy.array([5, 6, 7, 8])]) | np.vstack()
array([[1, 2, 3, 4],
... [5, 6, 7, 8]])
Plotting stages.
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience filter utility for corresponding function in pyplot.
Example:
>>> source([1, 2, 3, 4]) | plot.xlabel('x') | plot.ylabel('y') | plot.title('xy') | (plot.plot() | plot.savefig('foo.png'))
Convenience sink utility for corresponding function in pyplot.
Examples:
>>> source([1, 2, 3, 4]) | (pyplot.pie() | plot.savefig('pie.png'))
>>> source(range(100)) | (pyplot.acorr() | plot.savefig('acorr.png'))
Convenience sink utility for corresponding function in pyplot.
Examples:
>>> source([1, 2, 3, 4]) + source([2, 3, 6, 7]) | figure(0) | (plot.scatter() | plot.savefig('foo.png'))
>>> source([1, 2, 3, 4]) + source([2, 3, 6, 7]) | figure(1) | (plot.hexbin() | plot.savefig('bar.png'))
Convenience sink utility for corresponding function in pyplot.
Examples:
>>> source([1, 2, 3, 4]) | (pyplot.pie() | plot.savefig('pie.png'))
>>> source(range(100)) | (pyplot.acorr() | plot.savefig('acorr.png'))
Convenience sink utility for corresponding function in pyplot.
Examples:
>>> source([1, 2, 3, 4]) | plot.hold(True) | (plot.plot() | plot.savefig('foo.png'))
>>> source([1, 2, 3, 4]) | plot.hold(True) | (plot.plot() | plot.show())
Convenience sink utility for corresponding function in pyplot.
Examples:
>>> source([1, 2, 3, 4]) | (pyplot.pie() | plot.savefig('pie.png'))
>>> source(range(100)) | (pyplot.acorr() | plot.savefig('acorr.png'))
Convenience sink utility for pyplot’s plot.
Example:
>>> source([1, 2, 3, 4]) | plot.hold(True) | (plot.plot() | plot.savefig('foo.png'))
Convenience sink utility for corresponding function in pyplot.
Examples:
>>> source([1, 2, 3, 4]) | plot.hold(True) | (plot.plot() | plot.savefig('foo.png'))
>>> source([1, 2, 3, 4]) | plot.hold(True) | (plot.plot() | plot.show())
Convenience sink utility for corresponding function in pyplot.
Examples:
>>> source([1, 2, 3, 4]) + source([2, 3, 6, 7]) | figure(0) | (plot.scatter() | plot.savefig('foo.png'))
>>> source([1, 2, 3, 4]) + source([2, 3, 6, 7]) | figure(1) | (plot.hexbin() | plot.savefig('bar.png'))
Convenience sink utility for corresponding function in pyplot.
Examples:
>>> source([1, 2, 3, 4]) | plot.hold(True) | (plot.plot() | plot.savefig('foo.png'))
>>> source([1, 2, 3, 4]) | plot.hold(True) | (plot.plot() | plot.show())
Convenience sink utility for corresponding function in pyplot.
Examples:
>>> source([1, 2, 3, 4]) + source([2, 3, 6, 7]) | figure(0) | (plot.scatter() | plot.savefig('foo.png'))
>>> source([1, 2, 3, 4]) + source([2, 3, 6, 7]) | figure(1) | (plot.hexbin() | plot.savefig('bar.png'))