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], meaning any of the axes are of length 0.
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–only applicable to objects that are all numeric.
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.
agg(func, *args, **kwargs)
aggregate(func, *args, **kwargs)
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 axis (or axes) 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 TimeSeries to specified frequency.
asof(where[, subset])	The last row without any NaN is taken (or the last row without
astype(dtype[, copy, errors])	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 DataFrame.fillna(method='bfill')
bool()	Return the bool of a single element PandasObject.
clip([lower, upper, 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])	DEPRECATED: consolidate will be an internal implementation only.
convert_objects([convert_dates, ...])	Deprecated.
copy([deep])	Make a copy of this objects data.
count([axis])	Return number of observations over requested axis.
cummax([axis, skipna])	Return cumulative max over requested axis.
cummin([axis, skipna])	Return cumulative minimum over requested axis.
cumprod([axis, skipna])	Return cumulative product over requested axis.
cumsum([axis, skipna])	Return cumulative sum over requested axis.
describe([percentiles, include, exclude])	Generates descriptive statistics that summarize the central tendency, dispersion and shape of a dataset’s distribution, 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[, axis])	Wrapper for comparison method eq
equals(other)	Determines if two NDFrame objects contain the same elements.
ffill([axis, inplace, limit, downcast])	Synonym for DataFrame.fillna(method='ffill')
fillna([value, method, axis, inplace, ...])	Fill NA/NaN values using the specified method
filter([items, like, regex, axis])	Subset rows or columns of dataframe according to labels in the specified index.
first(offset)	Convenience method for subsetting initial periods of time series data based on a date offset.
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[, axis])	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[, axis])	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
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 Fisher’s definition of kurtosis (kurtosis of normal == 0.0).
kurtosis([axis, skipna, level, numeric_only])	Return unbiased kurtosis over requested axis using Fisher’s definition of kurtosis (kurtosis of normal == 0.0).
last(offset)	Convenience method for subsetting final periods of time series data based on a date offset.
le(other[, axis])	Wrapper for comparison method le
lt(other[, axis])	Wrapper for comparison method lt
mad([axis, skipna, level])	Return the mean absolute deviation of the values for the requested axis
major_xs(key)	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)	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[, axis])	Wrapper for comparison method ne
notnull()	Return a boolean same-sized object indicating if the values are not null.
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).
rank([axis, method, numeric_only, ...])	Compute numerical data ranks (1 through n) along axis.
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 indices 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 time series.
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).
round([decimals])	Round each value in Panel to a specified number of decimal places.
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([periods, freq, axis])	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([axis])	Squeeze length 1 dimensions.
std([axis, skipna, level, ddof, numeric_only])	Return sample 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)	Write the contained data to an HDF5 file using HDFStore.
to_json([path_or_buf, orient, date_format, ...])	Convert the object to a JSON string.
to_latex([buf, columns, col_space, header, ...])	Render an object to a tabular environment table.
to_long(*args, **kwargs)
to_msgpack([path_or_buf, encoding])	msgpack (serialize) object to input file path
to_pickle(path[, compression])	Pickle (serialize) object to input file path.
to_sparse(*args, **kwargs)	NOT IMPLEMENTED: do not call this method, as sparsifying is not supported for Panel objects and will raise an error.
to_sql(name, con[, flavor, schema, ...])	Write records stored in a DataFrame to a SQL database.
to_xarray()	Return an xarray object from the pandas object.
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 index value.
tshift([periods, freq, axis])
tz_convert(tz[, axis, level, copy])	Convert tz-aware axis to target time zone.
tz_localize(tz[, axis, level, copy, ambiguous])	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])	Return slice of panel along selected axis