Block dimensions for this dataset’s data or None if it’s not a dask array. |
|
|
Reduce this Dataset’s data by applying all along some dimension(s). |
|
Reduce this Dataset’s data by applying any along some dimension(s). |
|
Indices of the maxima of the member variables. |
|
Indices of the minima of the member variables. |
|
Return the coordinate label of the maximum value along a dimension. |
|
Return the coordinate label of the minimum value along a dimension. |
|
Reduce this Dataset’s data by applying max along some dimension(s). |
|
Reduce this Dataset’s data by applying min along some dimension(s). |
|
Reduce this Dataset’s data by applying mean along some dimension(s). |
|
Reduce this Dataset’s data by applying median along some dimension(s). |
|
Reduce this Dataset’s data by applying prod along some dimension(s). |
|
Reduce this Dataset’s data by applying sum along some dimension(s). |
|
Reduce this Dataset’s data by applying std along some dimension(s). |
|
Reduce this Dataset’s data by applying var along some dimension(s). |
Merge two sets of coordinates to create a new Dataset |
|
Convert these coordinates into a new Dataset |
|
Convert all index coordinates into a |
|
|
Reduce this DatasetCoarsen’s data by applying all along some dimension(s). |
|
Reduce this DatasetCoarsen’s data by applying any along some dimension(s). |
|
Reduce this DatasetCoarsen’s data by applying count along some dimension(s). |
|
Reduce this DatasetCoarsen’s data by applying max along some dimension(s). |
|
Reduce this DatasetCoarsen’s data by applying mean along some dimension(s). |
|
Reduce this DatasetCoarsen’s data by applying median along some dimension(s). |
|
Reduce this DatasetCoarsen’s data by applying min along some dimension(s). |
|
Reduce this DatasetCoarsen’s data by applying prod along some dimension(s). |
|
Reduce this DatasetCoarsen’s data by applying std along some dimension(s). |
|
Reduce this DatasetCoarsen’s data by applying sum along some dimension(s). |
|
Reduce this DatasetCoarsen’s data by applying var along some dimension(s). |
|
Assign data variables by group. |
Assign coordinates by group. |
|
|
Return the first element of each group along the group dimension |
|
Return the last element of each group along the group dimension |
Fill missing values in this object by group. |
|
Compute the qth quantile over each array in the groups and concatenate them together into a new array. |
|
|
Return elements from self or other depending on cond. |
Reduce this DatasetGroupBy’s data by applying all along some dimension(s). |
|
Reduce this DatasetGroupBy’s data by applying any along some dimension(s). |
|
Reduce this DatasetGroupBy’s data by applying count along some dimension(s). |
|
|
Reduce this DatasetGroupBy’s data by applying max along some dimension(s). |
|
Reduce this DatasetGroupBy’s data by applying mean along some dimension(s). |
|
Reduce this DatasetGroupBy’s data by applying median along some dimension(s). |
|
Reduce this DatasetGroupBy’s data by applying min along some dimension(s). |
|
Reduce this DatasetGroupBy’s data by applying prod along some dimension(s). |
|
Reduce this DatasetGroupBy’s data by applying std along some dimension(s). |
|
Reduce this DatasetGroupBy’s data by applying sum along some dimension(s). |
|
Reduce this DatasetGroupBy’s data by applying var along some dimension(s). |
Reduce this DatasetResample’s data by applying all along some dimension(s). |
|
Reduce this DatasetResample’s data by applying any along some dimension(s). |
|
|
Backward compatible implementation of |
|
Assign data variables by group. |
Assign coordinates by group. |
|
|
Backward fill new values at up-sampled frequency. |
Reduce this DatasetResample’s data by applying count along some dimension(s). |
|
|
Forward fill new values at up-sampled frequency. |
Fill missing values in this object by group. |
|
Return the first element of each group along the group dimension |
|
|
Return the last element of each group along the group dimension |
|
Apply a function over each Dataset in the groups generated for resampling and concatenate them together into a new Dataset. |
|
Reduce this DatasetResample’s data by applying max along some dimension(s). |
|
Reduce this DatasetResample’s data by applying mean along some dimension(s). |
|
Reduce this DatasetResample’s data by applying median along some dimension(s). |
|
Reduce this DatasetResample’s data by applying min along some dimension(s). |
|
Reduce this DatasetResample’s data by applying prod along some dimension(s). |
Compute the qth quantile over each array in the groups and concatenate them together into a new array. |
|
|
Reduce the items in this group by applying func along the pre-defined resampling dimension. |
|
Reduce this DatasetResample’s data by applying std along some dimension(s). |
|
Reduce this DatasetResample’s data by applying sum along some dimension(s). |
|
Reduce this DatasetResample’s data by applying var along some dimension(s). |
|
Return elements from self or other depending on cond. |
Reduce this object’s data windows by applying count along its dimension. |
|
|
Reduce this object’s data windows by applying max along its dimension. |
|
Reduce this object’s data windows by applying mean along its dimension. |
|
Reduce this object’s data windows by applying median along its dimension. |
|
Reduce this object’s data windows by applying min along its dimension. |
|
Reduce this object’s data windows by applying prod along its dimension. |
|
Reduce this object’s data windows by applying std along its dimension. |
|
Reduce this object’s data windows by applying sum along its dimension. |
|
Reduce this object’s data windows by applying var along its dimension. |
Exponentially weighted moving average |
|
|
Returns the indices that would sort this array. |
|
Copy of the array, cast to a specified type. |
|
Return an array whose values are limited to |
Complex-conjugate all elements. |
|
Return the complex conjugate, element-wise. |
|
|
|
|
Apply cumsum along some dimension of Dataset. |
|
Apply cumprod along some dimension of Dataset. |
|
Ranks the data. |
|
Create a new dataset from the contents of a backends.*DataStore object |
|
Store dataset contents to a backends.*DataStore object. |
Block dimensions for this array’s data or None if it’s not a dask array. |
|
|
Copy of the array, cast to a specified type. |
|
Copy an element of an array to a standard Python scalar and return it. |
|
Reduce this DataArray’s data by applying all along some dimension(s). |
|
Reduce this DataArray’s data by applying any along some dimension(s). |
|
Index or indices of the maximum of the DataArray over one or more dimensions. |
|
Index or indices of the minimum of the DataArray over one or more dimensions. |
|
Return the coordinate label of the maximum value along a dimension. |
|
Return the coordinate label of the minimum value along a dimension. |
|
Reduce this DataArray’s data by applying max along some dimension(s). |
|
Reduce this DataArray’s data by applying min along some dimension(s). |
|
Reduce this DataArray’s data by applying mean along some dimension(s). |
|
Reduce this DataArray’s data by applying median along some dimension(s). |
|
Reduce this DataArray’s data by applying prod along some dimension(s). |
|
Reduce this DataArray’s data by applying sum along some dimension(s). |
|
Reduce this DataArray’s data by applying std along some dimension(s). |
|
Reduce this DataArray’s data by applying var along some dimension(s). |
Merge two sets of coordinates to create a new Dataset |
|
Convert all index coordinates into a |
|
|
Reduce this DataArrayCoarsen’s data by applying all along some dimension(s). |
|
Reduce this DataArrayCoarsen’s data by applying any along some dimension(s). |
|
Reduce this DataArrayCoarsen’s data by applying count along some dimension(s). |
|
Reduce this DataArrayCoarsen’s data by applying max along some dimension(s). |
|
Reduce this DataArrayCoarsen’s data by applying mean along some dimension(s). |
|
Reduce this DataArrayCoarsen’s data by applying median along some dimension(s). |
|
Reduce this DataArrayCoarsen’s data by applying min along some dimension(s). |
|
Reduce this DataArrayCoarsen’s data by applying prod along some dimension(s). |
|
Reduce this DataArrayCoarsen’s data by applying std along some dimension(s). |
|
Reduce this DataArrayCoarsen’s data by applying sum along some dimension(s). |
|
Reduce this DataArrayCoarsen’s data by applying var along some dimension(s). |
Assign coordinates by group. |
|
Return the first element of each group along the group dimension |
|
|
Return the last element of each group along the group dimension |
Fill missing values in this object by group. |
|
Compute the qth quantile over each array in the groups and concatenate them together into a new array. |
|
|
Return elements from self or other depending on cond. |
|
Reduce this DataArrayGroupBy’s data by applying all along some dimension(s). |
|
Reduce this DataArrayGroupBy’s data by applying any along some dimension(s). |
|
Reduce this DataArrayGroupBy’s data by applying count along some dimension(s). |
|
Reduce this DataArrayGroupBy’s data by applying max along some dimension(s). |
|
Reduce this DataArrayGroupBy’s data by applying mean along some dimension(s). |
|
Reduce this DataArrayGroupBy’s data by applying median along some dimension(s). |
|
Reduce this DataArrayGroupBy’s data by applying min along some dimension(s). |
|
Reduce this DataArrayGroupBy’s data by applying prod along some dimension(s). |
|
Reduce this DataArrayGroupBy’s data by applying std along some dimension(s). |
|
Reduce this DataArrayGroupBy’s data by applying sum along some dimension(s). |
|
Reduce this DataArrayGroupBy’s data by applying var along some dimension(s). |
|
Reduce this DataArrayResample’s data by applying all along some dimension(s). |
|
Reduce this DataArrayResample’s data by applying any along some dimension(s). |
Backward compatible implementation of |
|
Assign coordinates by group. |
|
Backward fill new values at up-sampled frequency. |
|
|
Reduce this DataArrayResample’s data by applying count along some dimension(s). |
Forward fill new values at up-sampled frequency. |
|
Fill missing values in this object by group. |
|
Return the first element of each group along the group dimension |
|
Return the last element of each group along the group dimension |
|
|
Apply a function to each array in the group and concatenate them together into a new array. |
|
Reduce this DataArrayResample’s data by applying max along some dimension(s). |
|
Reduce this DataArrayResample’s data by applying mean along some dimension(s). |
Reduce this DataArrayResample’s data by applying median along some dimension(s). |
|
|
Reduce this DataArrayResample’s data by applying min along some dimension(s). |
|
Reduce this DataArrayResample’s data by applying prod along some dimension(s). |
Compute the qth quantile over each array in the groups and concatenate them together into a new array. |
|
Reduce the items in this group by applying func along some dimension(s). |
|
|
Reduce this DataArrayResample’s data by applying std along some dimension(s). |
|
Reduce this DataArrayResample’s data by applying sum along some dimension(s). |
|
Reduce this DataArrayResample’s data by applying var along some dimension(s). |
Return elements from self or other depending on cond. |
|
Reduce this object’s data windows by applying count along its dimension. |
|
|
Reduce this object’s data windows by applying max along its dimension. |
|
Reduce this object’s data windows by applying mean along its dimension. |
|
Reduce this object’s data windows by applying median along its dimension. |
|
Reduce this object’s data windows by applying min along its dimension. |
|
Reduce this object’s data windows by applying prod along its dimension. |
|
Reduce this object’s data windows by applying std along its dimension. |
|
Reduce this object’s data windows by applying sum along its dimension. |
|
Reduce this object’s data windows by applying var along its dimension. |
|
Returns the indices that would sort this array. |
|
Return an array whose values are limited to |
Complex-conjugate all elements. |
|
Return the complex conjugate, element-wise. |
|
|
Find indices where elements of v should be inserted in a to maintain order. |
|
|
|
Apply cumsum along some dimension of DataArray. |
|
Apply cumprod along some dimension of DataArray. |
|
Ranks the data. |
Round timestamps upward to specified frequency resolution. |
|
Round timestamps downward to specified frequency resolution. |
|
Round timestamps to specified frequency resolution. |
|
Return an array of formatted strings specified by date_format, which supports the same string format as the python standard library. |
|
The days of the datetime |
|
The day of the week with Monday=0, Sunday=6 |
|
The ordinal day of the year |
|
The number of days in the month |
|
The number of days in the month |
|
The hours of the datetime |
|
The microseconds of the datetime |
|
The minutes of the datetime |
|
The month as January=1, December=12 |
|
The nanoseconds of the datetime |
|
The quarter of the date |
|
Season of the year |
|
The seconds of the datetime |
|
Timestamps corresponding to datetimes |
|
The week ordinal of the year |
|
The day of the week with Monday=0, Sunday=6 |
|
The name of day in a week |
|
The week ordinal of the year |
|
The year of the datetime |
|
Convert strings in the array to be capitalized. |
|
Filling left and right side of strings in the array with an additional character. |
|
Test if pattern or regex is contained within a string of the array. |
|
Count occurrences of pattern in each string of the array. |
|
|
Decode character string in the array using indicated encoding. |
|
Encode character string in the array using indicated encoding. |
Test if the end of each string element matches a pattern. |
|
|
Return lowest or highest indexes in each strings in the array where the substring is fully contained between [start:end]. |
Extract element from indexable in each element in the array. |
|
Return lowest or highest indexes in each strings where the substring is fully contained between [start:end]. |
|
Check whether all characters in each string are alphanumeric. |
|
Check whether all characters in each string are alphabetic. |
|
Check whether all characters in each string are decimal. |
|
Check whether all characters in each string are digits. |
|
Check whether all characters in each string are lowercase. |
|
Check whether all characters in each string are numeric. |
|
Check whether all characters in each string are spaces. |
|
Check whether all characters in each string are titlecase. |
|
Check whether all characters in each string are uppercase. |
|
Compute the length of each element in the array. |
|
Filling right side of strings in the array with an additional character. |
|
Convert strings in the array to lowercase. |
|
Remove leading and trailing characters. |
|
Determine if each string matches a regular expression. |
|
Pad strings in the array up to width. |
|
Duplicate each string in the array. |
|
Replace occurrences of pattern/regex in the array with some string. |
|
Return highest indexes in each strings in the array where the substring is fully contained between [start:end]. |
|
Return highest indexes in each strings where the substring is fully contained between [start:end]. |
|
Filling left side of strings in the array with an additional character. |
|
Remove leading and trailing characters. |
|
Slice substrings from each element in the array. |
|
Replace a positional slice of a string with another value. |
|
Test if the start of each string element matches a pattern. |
|
Remove leading and trailing characters. |
|
Convert strings in the array to be swapcased. |
|
Convert strings in the array to titlecase. |
|
Map all characters in the string through the given mapping table. |
|
Convert strings in the array to uppercase. |
|
|
Wrap long strings in the array to be formatted in paragraphs with length less than a given width. |
Pad strings in the array by prepending ‘0’ characters. |
|
|
Reduce this Variable’s data by applying all along some dimension(s). |
|
Reduce this Variable’s data by applying any along some dimension(s). |
|
Index or indices of the maximum of the Variable over one or more dimensions. |
|
Index or indices of the minimum of the Variable over one or more dimensions. |
|
Returns the indices that would sort this array. |
|
Copy of the array, cast to a specified type. |
|
True if two Variables have the values after being broadcast against each other; otherwise False. |
|
Coerce this array’s data into a dask arrays with the given chunks. |
|
Return an array whose values are limited to |
|
Apply reduction function. |
|
Manually trigger loading of this variable’s data from disk or a remote source into memory and return a new variable. |
|
Concatenate variables along a new or existing dimension. |
Complex-conjugate all elements. |
|
Return the complex conjugate, element-wise. |
|
|
Returns a copy of this object. |
|
Reduce this Variable’s data by applying count along some dimension(s). |
|
Apply cumprod along some dimension of Variable. |
|
Apply cumsum along some dimension of Variable. |
|
True if two Variables have the same dimensions and values; otherwise False. |
|
|
Return axis number(s) corresponding to dimension(s) in this array. |
|
|
Like equals, but also checks attributes. |
|
Return a new array indexed along the specified dimension(s). |
|
|
|
Copy an element of an array to a standard Python scalar and return it. |
|
Manually trigger loading of this variable’s data from disk or a remote source into memory and return this variable. |
|
Reduce this Variable’s data by applying max along some dimension(s). |
|
Reduce this Variable’s data by applying mean along some dimension(s). |
|
Reduce this Variable’s data by applying median along some dimension(s). |
|
Reduce this Variable’s data by applying min along some dimension(s). |
|
True if the intersection of two Variable’s non-null data is equal; otherwise false. |
|
|
|
Reduce this Variable’s data by applying prod along some dimension(s). |
|
Compute the qth quantile of the data along the specified dimension. |
|
Ranks the data. |
|
Reduce this array by applying func along some dimension(s). |
|
Return a new Variable with rolld data. |
|
Make a rolling_window along dim and add a new_dim to the last place. |
|
|
|
Find indices where elements of v should be inserted in a to maintain order. |
|
Return a new variable with given set of dimensions. |
|
Return a new Variable with shifted data. |
|
Return a new object with squeezed data. |
|
Stack any number of existing dimensions into a single new dimension. |
|
Reduce this Variable’s data by applying std along some dimension(s). |
|
Reduce this Variable’s data by applying sum along some dimension(s). |
Return this variable as a base xarray.Variable |
|
to_coord has been deprecated. |
|
|
Dictionary representation of variable. |
Convert this variable to a pandas.Index |
|
Return this variable as an xarray.IndexVariable |
|
to_variable has been deprecated. |
|
|
Return a new Variable object with transposed dimensions. |
|
Unstack an existing dimension into multiple new dimensions. |
|
Reduce this Variable’s data by applying var along some dimension(s). |
|
|
Dictionary of local attributes on this variable. |
|
Block dimensions for this array’s data or None if it’s not a dask array. |
|
Tuple of dimension names with which this variable is associated. |
|
Dictionary of encodings on this variable. |
|
Ordered mapping from dimension names to lengths. |
|
The variable’s data as a numpy.ndarray |
|
|
Reduce this Variable’s data by applying all along some dimension(s). |
|
Reduce this Variable’s data by applying any along some dimension(s). |
|
Returns the indices that would sort this array. |
|
Copy of the array, cast to a specified type. |
|
True if two Variables have the values after being broadcast against each other; otherwise False. |
|
Coerce this array’s data into a dask arrays with the given chunks. |
|
Return an array whose values are limited to |
|
Apply reduction function. |
|
Manually trigger loading of this variable’s data from disk or a remote source into memory and return a new variable. |
|
Specialized version of Variable.concat for IndexVariable objects. |
Complex-conjugate all elements. |
|
Return the complex conjugate, element-wise. |
|
|
Returns a copy of this object. |
|
Reduce this Variable’s data by applying count along some dimension(s). |
|
Apply cumprod along some dimension of Variable. |
|
Apply cumsum along some dimension of Variable. |
|
True if two Variables have the same dimensions and values; otherwise False. |
|
|
Return axis number(s) corresponding to dimension(s) in this array. |
|
Return a new IndexVariable from a given MultiIndex level. |
|
|
Like equals, but also checks attributes. |
|
Return a new array indexed along the specified dimension(s). |
|
|
|
Copy an element of an array to a standard Python scalar and return it. |
Manually trigger loading of this variable’s data from disk or a remote source into memory and return this variable. |
|
|
Reduce this Variable’s data by applying max along some dimension(s). |
|
Reduce this Variable’s data by applying mean along some dimension(s). |
|
Reduce this Variable’s data by applying median along some dimension(s). |
|
Reduce this Variable’s data by applying min along some dimension(s). |
|
True if the intersection of two Variable’s non-null data is equal; otherwise false. |
|
|
|
Reduce this Variable’s data by applying prod along some dimension(s). |
|
Compute the qth quantile of the data along the specified dimension. |
|
Ranks the data. |
|
Reduce this array by applying func along some dimension(s). |
|
Return a new Variable with rolld data. |
|
Make a rolling_window along dim and add a new_dim to the last place. |
|
|
|
Find indices where elements of v should be inserted in a to maintain order. |
|
Return a new variable with given set of dimensions. |
|
Return a new Variable with shifted data. |
|
Return a new object with squeezed data. |
|
Stack any number of existing dimensions into a single new dimension. |
|
Reduce this Variable’s data by applying std along some dimension(s). |
|
Reduce this Variable’s data by applying sum along some dimension(s). |
Return this variable as a base xarray.Variable |
|
to_coord has been deprecated. |
|
|
Dictionary representation of variable. |
Convert this variable to a pandas.Index |
|
Return this variable as an xarray.IndexVariable |
|
to_variable has been deprecated. |
|
|
Return a new Variable object with transposed dimensions. |
|
Unstack an existing dimension into multiple new dimensions. |
|
Reduce this Variable’s data by applying var along some dimension(s). |
|
|
Dictionary of local attributes on this variable. |
|
Block dimensions for this array’s data or None if it’s not a dask array. |
|
Tuple of dimension names with which this variable is associated. |
|
Dictionary of encodings on this variable. |
|
Return MultiIndex level names or None if this IndexVariable has no MultiIndex. |
|
Ordered mapping from dimension names to lengths. |
|
The variable’s data as a numpy.ndarray |
|
xarray specific variant of numpy.angle. |
|
xarray specific variant of numpy.arccos. |
|
xarray specific variant of numpy.arccosh. |
|
xarray specific variant of numpy.arcsin. |
|
xarray specific variant of numpy.arcsinh. |
|
xarray specific variant of numpy.arctan. |
|
xarray specific variant of numpy.arctan2. |
|
xarray specific variant of numpy.arctanh. |
|
xarray specific variant of numpy.ceil. |
|
xarray specific variant of numpy.conj. |
|
xarray specific variant of numpy.copysign. |
|
xarray specific variant of numpy.cos. |
|
xarray specific variant of numpy.cosh. |
|
xarray specific variant of numpy.deg2rad. |
|
xarray specific variant of numpy.degrees. |
|
xarray specific variant of numpy.exp. |
|
xarray specific variant of numpy.expm1. |
|
xarray specific variant of numpy.fabs. |
|
xarray specific variant of numpy.fix. |
|
xarray specific variant of numpy.floor. |
|
xarray specific variant of numpy.fmax. |
|
xarray specific variant of numpy.fmin. |
|
xarray specific variant of numpy.fmod. |
|
xarray specific variant of numpy.fmod. |
|
xarray specific variant of numpy.frexp. |
|
xarray specific variant of numpy.hypot. |
|
xarray specific variant of numpy.imag. |
|
xarray specific variant of numpy.iscomplex. |
|
xarray specific variant of numpy.isfinite. |
|
xarray specific variant of numpy.isinf. |
|
xarray specific variant of numpy.isnan. |
|
xarray specific variant of numpy.isreal. |
|
xarray specific variant of numpy.ldexp. |
|
xarray specific variant of numpy.log. |
|
xarray specific variant of numpy.log10. |
|
xarray specific variant of numpy.log1p. |
|
xarray specific variant of numpy.log2. |
|
xarray specific variant of numpy.logaddexp. |
|
xarray specific variant of numpy.logaddexp2. |
|
xarray specific variant of numpy.logical_and. |
|
xarray specific variant of numpy.logical_not. |
|
xarray specific variant of numpy.logical_or. |
|
xarray specific variant of numpy.logical_xor. |
|
xarray specific variant of numpy.maximum. |
|
xarray specific variant of numpy.minimum. |
|
xarray specific variant of numpy.nextafter. |
|
xarray specific variant of numpy.rad2deg. |
|
xarray specific variant of numpy.radians. |
|
xarray specific variant of numpy.real. |
|
xarray specific variant of numpy.rint. |
|
xarray specific variant of numpy.sign. |
|
xarray specific variant of numpy.signbit. |
|
xarray specific variant of numpy.sin. |
|
xarray specific variant of numpy.sinh. |
|
xarray specific variant of numpy.sqrt. |
|
xarray specific variant of numpy.square. |
|
xarray specific variant of numpy.tan. |
|
xarray specific variant of numpy.tanh. |
|
xarray specific variant of numpy.trunc. |
|
|
Apply a plotting function to a 2d facet’s subset of the data. |
|
Draw titles either above each facet or on the grid margins. |
|
Set and control tick behavior |
|
Apply a plotting function to each facet’s subset of the data. |
|
Return whether all elements are True. |
|
Return whether any element is True. |
|
Append a collection of Index options together. |
|
Return the integer indices that would sort the index. |
|
Return the label from the index, or, if not present, the previous one. |
|
Find the locations (indices) of the labels from the index for every entry in the where argument. |
|
Create an Index with values cast to dtypes. |
|
Needed for .loc based partial-string indexing |
|
Make a copy of this object. |
|
Make new Index with passed location(-s) deleted. |
|
Return a new Index with elements from the index that are not in other. |
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Make new Index with passed list of labels deleted. |
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Return Index with duplicate values removed. |
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Return index with requested level(s) removed. |
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Return Index without NA/NaN values |
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Indicate duplicate index values. |
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Determine if two Index objects contain the same elements. |
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Encode the object as an enumerated type or categorical variable. |
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Fill NA/NaN values with the specified value |
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Render a string representation of the Index. |
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Compute indexer and mask for new index given the current index. |
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Guaranteed return of an indexer even when non-unique. |
Compute indexer and mask for new index given the current index. |
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Return an Index of values for requested level. |
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Adapted from pandas.tseries.index.DatetimeIndex.get_loc |
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Calculate slice bound that corresponds to given label. |
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Adapted from pandas.tseries.index.DatetimeIndex.get_value |
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Group the index labels by a given array of values. |
Whether the type is an integer type. |
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Similar to equals, but check that other comparable attributes are also equal. |
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Make new Index inserting new item at location. |
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Form the intersection of two Index objects. |
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More flexible, faster check like |
Check if the Index holds categorical data. |
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Whether the index type is compatible with the provided type. |
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Return a boolean array where the index values are in values. |
Detect missing values. |
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Detect missing values. |
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Return the first element of the underlying data as a python scalar. |
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Compute join_index and indexers to conform data structures to the new index. |
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Map values using input correspondence (a dict, Series, or function). |
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Return the maximum value of the Index. |
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Memory usage of the values |
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Return the minimum value of the Index. |
Detect existing (non-missing) values. |
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Detect existing (non-missing) values. |
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Return number of unique elements in the object. |
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Return a new Index of the values set with the mask. |
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Return an ndarray of the flattened values of the underlying data. |
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Create index with target’s values (move/add/delete values as necessary). |
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Alter Index or MultiIndex name. |
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Repeat elements of a Index. |
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Find indices where elements should be inserted to maintain order. |
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Set Index or MultiIndex name. |
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Fast lookup of value from 1-dimensional ndarray. |
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Shift the CFTimeIndex a multiple of the given frequency. |
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For an ordered or unique index, compute the slice indexer for input labels and step. |
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Compute slice locations for input labels. |
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Use sort_values instead. |
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Return a sorted copy of the index. |
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For internal compatibility with with the Index API. |
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Return an Index of formatted strings specified by date_format, which supports the same string format as the python standard library. |
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Compute the symmetric difference of two Index objects. |
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Return a new Index of the values selected by the indices. |
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If possible, convert this index to a pandas.DatetimeIndex. |
Identity method. |
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Create a DataFrame with a column containing the Index. |
Return a list of the values. |
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Format specified values of self and return them. |
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A NumPy ndarray representing the values in this Series or Index. |
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Create a Series with both index and values equal to the index keys useful with map for returning an indexer based on an index. |
Return a list of the values. |
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Return the transpose, which is by definition self. |
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Form the union of two Index objects. |
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Return unique values in the index. |
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Return a Series containing counts of unique values. |
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Return an Index of same shape as self and whose corresponding entries are from self where cond is True and otherwise are from other. |
Return the transpose, which is by definition self. |
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The ExtensionArray of the data backing this Series or Index. |
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Convert to integers with units of microseconds since 1970-01-01. |
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The days of the datetime |
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The day of week of the datetime |
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The ordinal day of year of the datetime |
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Return the dtype object of the underlying data. |
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Return if I have any nans; enables various perf speedups. |
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The hours of the datetime |
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Return a string of the type inferred from the values. |
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Alias for is_monotonic_increasing. |
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Return if the index is monotonic increasing (only equal or increasing) values. |
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Return if the index is monotonic decreasing (only equal or decreasing) values. |
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Return if the index has unique values. |
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The microseconds of the datetime |
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The minutes of the datetime |
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The month of the datetime |
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Return the number of bytes in the underlying data. |
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Number of dimensions of the underlying data, by definition 1. |
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Number of levels. |
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The seconds of the datetime |
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Return a tuple of the shape of the underlying data. |
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Return the number of elements in the underlying data. |
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Return an array representing the data in the Index. |
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The year of the datetime |
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Encode the variables and attributes in this store |
encode one attribute |
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encode one variable |
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This loads the variables and attributes simultaneously. |
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This provides a centralized method to set the dataset attributes on the data store. |
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This provides a centralized method to set the dimensions on the data store. |
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This provides a centralized method to set the variables on the data store. |
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Top level method for putting data on this store, this method: |
in stores, variables are all variables AND coordinates in xarray.Dataset variables are variables NOT coordinates, so here we pass the whole dataset in instead of doing dataset.variables |
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Encode the variables and attributes in this store |
encode one attribute |
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encode one variable |
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This loads the variables and attributes simultaneously. |
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This provides a centralized method to set the dataset attributes on the data store. |
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This provides a centralized method to set the dimensions on the data store. |
This provides a centralized method to set the variables on the data store. |
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Top level method for putting data on this store, this method: |
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in stores, variables are all variables AND coordinates in xarray.Dataset variables are variables NOT coordinates, so here we pass the whole dataset in instead of doing dataset.variables |
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This loads the variables and attributes simultaneously. |
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Encode the variables and attributes in this store |
encode one attribute |
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encode one variable |
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This loads the variables and attributes simultaneously. |
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This provides a centralized method to set the dataset attributes on the data store. |
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This provides a centralized method to set the dimensions on the data store. |
This provides a centralized method to set the variables on the data store. |
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Top level method for putting data on this store, this method: |
in stores, variables are all variables AND coordinates in xarray.Dataset variables are variables NOT coordinates, so here we pass the whole dataset in instead of doing dataset.variables |
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Acquire the file object from this manager. |
Context manager for acquiring a file. |
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Close the file object associated with this manager, if needed. |
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Acquire a file object from the manager. |
Context manager for acquiring a file. |
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Explicitly close any associated file object (if necessary). |
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Acquire the file object from this manager. |
Context manager for acquiring a file. |
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Close the file object associated with this manager, if needed. |