pandas.Panel

class pandas.Panel(data=None, items=None, major_axis=None, minor_axis=None, copy=False, dtype=None)

Represents wide format panel data, stored as 3-dimensional array

Parameters:

data : ndarray (items x major x minor), or dict of DataFrames

items : Index or array-like

axis=0

major_axis : Index or array-like

axis=1

minor_axis : Index or array-like

axis=2

dtype : dtype, default None

Data type to force, otherwise infer

copy : boolean, default False

Copy data from inputs. Only affects DataFrame / 2d ndarray input

Attributes

at	Fast label-based scalar accessor
axes	Return index label(s) of the internal NDFrame
blocks	Internal property, property synonym for as_blocks()
dtypes	Return the dtypes in this object
empty	True if NDFrame is entirely empty [no items]
ftypes	Return the ftypes (indication of sparse/dense and dtype) in this object.
iat	Fast integer location scalar accessor.
iloc	Purely integer-location based indexing for selection by position.
is_copy
ix	A primarily label-location based indexer, with integer position fallback.
loc	Purely label-location based indexer for selection by label.
ndim	Number of axes / array dimensions
shape	Return a tuple of axis dimensions
size	number of elements in the NDFrame
values	Numpy representation of NDFrame

Methods

abs()	Return an object with absolute value taken.
add(other[, axis])	Addition of series and other, element-wise (binary operator add).
add_prefix(prefix)	Concatenate prefix string with panel items names.
add_suffix(suffix)	Concatenate suffix string with panel items names
align(other, **kwargs)
all([axis, bool_only, skipna, level])	Return whether all elements are True over requested axis
any([axis, bool_only, skipna, level])	Return whether any element is True over requested axis
apply(func[, axis])	Applies function along input axis of the Panel
as_blocks([copy])	Convert the frame to a dict of dtype -> Constructor Types that each has a homogeneous dtype.
as_matrix()
asfreq(freq[, method, how, normalize])	Convert all TimeSeries inside to specified frequency using DateOffset objects.
astype(dtype[, copy, raise_on_error])	Cast object to input numpy.dtype
at_time(time[, asof])	Select values at particular time of day (e.g.
between_time(start_time, end_time[, ...])	Select values between particular times of the day (e.g., 9:00-9:30 AM)
bfill([axis, inplace, limit, downcast])	Synonym for NDFrame.fillna(method=’bfill’)
bool()	Return the bool of a single element PandasObject
clip([lower, upper, out, axis])	Trim values at input threshold(s)
clip_lower(threshold[, axis])	Return copy of the input with values below given value(s) truncated
clip_upper(threshold[, axis])	Return copy of input with values above given value(s) truncated
compound([axis, skipna, level])	Return the compound percentage of the values for the requested axis
conform(frame[, axis])	Conform input DataFrame to align with chosen axis pair.
consolidate([inplace])	Compute NDFrame with “consolidated” internals (data of each dtype grouped together in a single ndarray).
convert_objects([convert_dates, ...])	Attempt to infer better dtype for object columns
copy([deep])	Make a copy of this object
count([axis])	Return number of observations over requested axis.
cummax([axis, dtype, out, skipna])	Return cumulative max over requested axis.
cummin([axis, dtype, out, skipna])	Return cumulative min over requested axis.
cumprod([axis, dtype, out, skipna])	Return cumulative prod over requested axis.
cumsum([axis, dtype, out, skipna])	Return cumulative sum over requested axis.
describe([percentiles, include, exclude])	Generate various summary statistics, excluding NaN values.
div(other[, axis])	Floating division of series and other, element-wise (binary operator truediv).
divide(other[, axis])	Floating division of series and other, element-wise (binary operator truediv).
drop(labels[, axis, level, inplace, errors])	Return new object with labels in requested axis removed
dropna([axis, how, inplace])	Drop 2D from panel, holding passed axis constant
eq(other)	Wrapper for comparison method eq
equals(other)	Determines if two NDFrame objects contain the same elements.
ffill([axis, inplace, limit, downcast])	Synonym for NDFrame.fillna(method=’ffill’)
fillna([value, method, axis, inplace, ...])	Fill NA/NaN values using the specified method
filter([items, like, regex, axis])	Restrict the info axis to set of items or wildcard
first(offset)	Convenience method for subsetting initial periods of time series data
floordiv(other[, axis])	Integer division of series and other, element-wise (binary operator floordiv).
fromDict(data[, intersect, orient, dtype])	Construct Panel from dict of DataFrame objects
from_dict(data[, intersect, orient, dtype])	Construct Panel from dict of DataFrame objects
ge(other)	Wrapper for comparison method ge
get(key[, default])	Get item from object for given key (DataFrame column, Panel slice, etc.).
get_dtype_counts()	Return the counts of dtypes in this object
get_ftype_counts()	Return the counts of ftypes in this object
get_value(*args, **kwargs)	Quickly retrieve single value at (item, major, minor) location
get_values()	same as values (but handles sparseness conversions)
groupby(function[, axis])	Group data on given axis, returning GroupBy object
gt(other)	Wrapper for comparison method gt
head([n])
interpolate([method, axis, limit, inplace, ...])	Interpolate values according to different methods.
isnull()	Return a boolean same-sized object indicating if the values are null
iteritems()	Iterate over (label, values) on info axis
iterkv(*args, **kwargs)	iteritems alias used to get around 2to3. Deprecated
join(other[, how, lsuffix, rsuffix])	Join items with other Panel either on major and minor axes column
keys()	Get the ‘info axis’ (see Indexing for more)
kurt([axis, skipna, level, numeric_only])	Return unbiased kurtosis over requested axis using Fishers definition of kurtosis (kurtosis of normal == 0.0).
kurtosis([axis, skipna, level, numeric_only])	Return unbiased kurtosis over requested axis using Fishers definition of kurtosis (kurtosis of normal == 0.0).
last(offset)	Convenience method for subsetting final periods of time series data
le(other)	Wrapper for comparison method le
lt(other)	Wrapper for comparison method lt
mad([axis, skipna, level])	Return the mean absolute deviation of the values for the requested axis
major_xs(key[, copy])	Return slice of panel along major axis
mask(cond[, other, inplace, axis, level, ...])	Return an object of same shape as self and whose corresponding entries are from self where cond is False and otherwise are from other.
max([axis, skipna, level, numeric_only])	This method returns the maximum of the values in the object.
mean([axis, skipna, level, numeric_only])	Return the mean of the values for the requested axis
median([axis, skipna, level, numeric_only])	Return the median of the values for the requested axis
min([axis, skipna, level, numeric_only])	This method returns the minimum of the values in the object.
minor_xs(key[, copy])	Return slice of panel along minor axis
mod(other[, axis])	Modulo of series and other, element-wise (binary operator mod).
mul(other[, axis])	Multiplication of series and other, element-wise (binary operator mul).
multiply(other[, axis])	Multiplication of series and other, element-wise (binary operator mul).
ne(other)	Wrapper for comparison method ne
notnull()	Return a boolean same-sized object indicating if the values are
pct_change([periods, fill_method, limit, freq])	Percent change over given number of periods.
pipe(func, *args, **kwargs)	Apply func(self, *args, **kwargs)
pop(item)	Return item and drop from frame.
pow(other[, axis])	Exponential power of series and other, element-wise (binary operator pow).
prod([axis, skipna, level, numeric_only])	Return the product of the values for the requested axis
product([axis, skipna, level, numeric_only])	Return the product of the values for the requested axis
radd(other[, axis])	Addition of series and other, element-wise (binary operator radd).
rdiv(other[, axis])	Floating division of series and other, element-wise (binary operator rtruediv).
reindex([items, major_axis, minor_axis])	Conform Panel to new index with optional filling logic, placing NA/NaN in locations having no value in the previous index.
reindex_axis(labels[, axis, method, level, ...])	Conform input object to new index with optional filling logic, placing NA/NaN in locations having no value in the previous index.
reindex_like(other[, method, copy, limit, ...])	return an object with matching indicies to myself
rename([items, major_axis, minor_axis])	Alter axes input function or functions.
rename_axis(mapper[, axis, copy, inplace])	Alter index and / or columns using input function or functions.
replace([to_replace, value, inplace, limit, ...])	Replace values given in ‘to_replace’ with ‘value’.
resample(rule[, how, axis, fill_method, ...])	Convenience method for frequency conversion and resampling of regular time-series data.
rfloordiv(other[, axis])	Integer division of series and other, element-wise (binary operator rfloordiv).
rmod(other[, axis])	Modulo of series and other, element-wise (binary operator rmod).
rmul(other[, axis])	Multiplication of series and other, element-wise (binary operator rmul).
rpow(other[, axis])	Exponential power of series and other, element-wise (binary operator rpow).
rsub(other[, axis])	Subtraction of series and other, element-wise (binary operator rsub).
rtruediv(other[, axis])	Floating division of series and other, element-wise (binary operator rtruediv).
sample([n, frac, replace, weights, ...])	Returns a random sample of items from an axis of object.
select(crit[, axis])	Return data corresponding to axis labels matching criteria
sem([axis, skipna, level, ddof, numeric_only])	Return unbiased standard error of the mean over requested axis.
set_axis(axis, labels)	public verson of axis assignment
set_value(*args, **kwargs)	Quickly set single value at (item, major, minor) location
shift(*args, **kwargs)	Shift index by desired number of periods with an optional time freq.
skew([axis, skipna, level, numeric_only])	Return unbiased skew over requested axis
slice_shift([periods, axis])	Equivalent to shift without copying data.
sort_index([axis, level, ascending, ...])	Sort object by labels (along an axis)
sort_values(by[, axis, ascending, inplace, ...])
squeeze()	squeeze length 1 dimensions
std([axis, skipna, level, ddof, numeric_only])	Return unbiased standard deviation over requested axis.
sub(other[, axis])	Subtraction of series and other, element-wise (binary operator sub).
subtract(other[, axis])	Subtraction of series and other, element-wise (binary operator sub).
sum([axis, skipna, level, numeric_only])	Return the sum of the values for the requested axis
swapaxes(axis1, axis2[, copy])	Interchange axes and swap values axes appropriately
swaplevel(i, j[, axis])	Swap levels i and j in a MultiIndex on a particular axis
tail([n])
take(indices[, axis, convert, is_copy])	Analogous to ndarray.take
toLong(*args, **kwargs)
to_clipboard([excel, sep])	Attempt to write text representation of object to the system clipboard This can be pasted into Excel, for example.
to_dense()	Return dense representation of NDFrame (as opposed to sparse)
to_excel(path[, na_rep, engine])	Write each DataFrame in Panel to a separate excel sheet
to_frame([filter_observations])	Transform wide format into long (stacked) format as DataFrame whose columns are the Panel’s items and whose index is a MultiIndex formed of the Panel’s major and minor axes.
to_hdf(path_or_buf, key, **kwargs)	activate the HDFStore
to_json([path_or_buf, orient, date_format, ...])	Convert the object to a JSON string.
to_long(*args, **kwargs)
to_msgpack([path_or_buf])	msgpack (serialize) object to input file path
to_pickle(path)	Pickle (serialize) object to input file path
to_sparse([fill_value, kind])	Convert to SparsePanel
to_sql(name, con[, flavor, schema, ...])	Write records stored in a DataFrame to a SQL database.
transpose(*args, **kwargs)	Permute the dimensions of the Panel
truediv(other[, axis])	Floating division of series and other, element-wise (binary operator truediv).
truncate([before, after, axis, copy])	Truncates a sorted NDFrame before and/or after some particular dates.
tshift([periods, freq, axis])
tz_convert(tz[, axis, level, copy])	Convert tz-aware axis to target time zone.
tz_localize(*args, **kwargs)	Localize tz-naive TimeSeries to target time zone
update(other[, join, overwrite, ...])	Modify Panel in place using non-NA values from passed Panel, or object coercible to Panel.
var([axis, skipna, level, ddof, numeric_only])	Return unbiased variance over requested axis.
where(cond[, other, inplace, axis, level, ...])	Return an object of same shape as self and whose corresponding entries are from self where cond is True and otherwise are from other.
xs(key[, axis, copy])	Return slice of panel along selected axis