Deedle
FrameExtensions Type
Contains C# and F# extension methods for the `Frame<'R, 'C>` type. The members are automatically available when you import the `Deedle` namespace. The type contains object-oriented counterparts to most of the functionality from the `Frame` module.
Data structure manipulation:
Summary 1
Input and output:
Summary 2
Missing values:
Summary 3
Table of contents
- Other module members
- Data structure manipulation
- Fancy accessors
- Frame operations
- Frame transformations
- Input and output
- Missing values
Other module members
Static members
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Description
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Full Usage:
FrameExtensions.Diff(frame, offset)
Parameters:
Frame<'TRowKey, 'TColumnKey>
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The input frame containing at least some `float` columns.
offset : int
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When positive, subtracts the past values from the current values; when negative, subtracts the future values from the current values.
Returns: Frame<'TRowKey, 'TColumnKey>
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Returns a frame with columns containing difference between an original value and a value at the specified offset. For example, calling `Frame.diff 1 s` returns a frame where previous column values is subtracted from the current ones. In pseudo-code, the function behaves as follows: result[k] = series[k] - series[k - offset] Columns that cannot be converted to `float` are left without a change.
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Full Usage:
FrameExtensions.GetSlice(series, lo1, hi1, lo2, hi2)
Parameters:
ColumnSeries<'TRowKey, ('TColKey1 * 'TColKey2)>
lo1 : 'K1 option
hi1 : 'K1 option
lo2 : 'K2 option
hi2 : 'K2 option
Returns: Frame<'TRowKey, ('TColKey1 * 'TColKey2)>
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Full Usage:
FrameExtensions.GetSlice(series, k1, lo2, hi2)
Parameters:
ColumnSeries<'TRowKey, ('TColKey1 * 'TColKey2)>
k1 : 'TColKey1
lo2 : 'TColKey2 option
hi2 : 'TColKey2 option
Returns: Frame<'TRowKey, ('TColKey1 * 'TColKey2)>
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Full Usage:
FrameExtensions.GetSlice(series, lo1, hi1, k2)
Parameters:
ColumnSeries<'TRowKey, ('TColKey1 * 'TColKey2)>
lo1 : 'TColKey1 option
hi1 : 'TColKey1 option
k2 : 'TColKey2
Returns: Frame<'TRowKey, ('TColKey1 * 'TColKey2)>
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Full Usage:
FrameExtensions.GetSlice(series, lo1, hi1, lo2, hi2)
Parameters:
ColumnSeries<'TRowKey, ('TColKey1 * 'TColKey2)>
lo1 : 'TColKey1 option
hi1 : 'TColKey1 option
lo2 : 'TColKey2 option
hi2 : 'TColKey2 option
Returns: Frame<'TRowKey, ('TColKey1 * 'TColKey2)>
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Full Usage:
FrameExtensions.PctChange(frame, offset)
Parameters:
Frame<'TRowKey, 'TColumnKey>
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The input frame containing at least some float columns.
offset : int
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When positive, computes change from past values; when negative, computes change relative to future values.
Returns: Frame<'TRowKey, 'TColumnKey>
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Returns a frame where each value is the percentage change relative to the value at the
specified offset. For example, calling
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Full Usage:
FrameExtensions.Print(frame, printTypes)
Parameters:
Frame<'K, 'V>
printTypes : bool
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Full Usage:
FrameExtensions.Select(frame, projection)
Parameters:
Frame<'TRowKey, 'TColumnKey>
projection : Func<KeyValuePair<'TRowKey, ObjectSeries<'TColumnKey>>, int, 'a>
Returns: Frame<'TRowKey, 'b>
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Full Usage:
FrameExtensions.Select(frame, projection)
Parameters:
Frame<'TRowKey, 'TColumnKey>
projection : Func<KeyValuePair<'TRowKey, ObjectSeries<'TColumnKey>>, 'a>
Returns: Frame<'TRowKey, 'b>
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Full Usage:
FrameExtensions.SelectColumnKeys(frame, projection)
Parameters:
Frame<'TRowKey, 'TColumnKey>
projection : Func<KeyValuePair<'TColumnKey, OptionalValue<ObjectSeries<'TRowKey>>>, 'a>
Returns: Frame<'TRowKey, 'a>
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Full Usage:
FrameExtensions.SelectRowKeys(frame, projection)
Parameters:
Frame<'TRowKey, 'TColumnKey>
projection : Func<KeyValuePair<'TRowKey, OptionalValue<ObjectSeries<'TColumnKey>>>, 'a>
Returns: Frame<'a, 'TColumnKey>
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Returns a frame with columns shifted by the specified offset. When the offset is positive, the values are shifted forward and first `offset` keys are dropped. When the offset is negative, the values are shifted backwards and the last `offset` keys are dropped. Expressed in pseudo-code: result[k] = series[k - offset] If you want to calculate the difference, e.g. `df - (Frame.shift 1 df)`, you can use `Frame.diff` which will be a little bit faster.
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Full Usage:
FrameExtensions.Where(frame, condition)
Parameters:
Frame<'TRowKey, 'TColumnKey>
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A data frame to invoke the filtering function on.
condition : Func<KeyValuePair<'TRowKey, ObjectSeries<'TColumnKey>>, int, bool>
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A delegate that specifies the filtering condition.
Returns: Frame<'TRowKey, 'TColumnKey>
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Filters frame rows using the specified condtion. Returns a new data frame that contains rows for which the provided function returned false. The function is called with `KeyValuePair` containing the row key as the `Key` and `Value` gives access to the row series and a row index.
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Full Usage:
FrameExtensions.Where(frame, condition)
Parameters:
Frame<'TRowKey, 'TColumnKey>
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A data frame to invoke the filtering function on.
condition : Func<KeyValuePair<'TRowKey, ObjectSeries<'TColumnKey>>, bool>
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A delegate that specifies the filtering condition.
Returns: Frame<'TRowKey, 'TColumnKey>
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Filters frame rows using the specified condition. Returns a new data frame that contains rows for which the provided function returned false. The function is called with `KeyValuePair` containing the row key as the `Key` and `Value` gives access to the row series.
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Data structure manipulation
Static members
| Static member |
Description
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Creates a new data frame where the specified columns are expanded based on runtime
structure of the objects they store. A column can be expanded if it is
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Full Usage:
FrameExtensions.ExpandColumns(frame, nesting, ?dynamic)
Parameters:
Frame<'R, string>
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Input data frame to be expanded.
nesting : int
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The nesting level for expansion. When set to 0, nothing is done.
?dynamic : bool
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Specifies whether to use dynamic expansion.
Returns: Frame<'R, string>
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Creates a new data frame where all columns are expanded based on runtime
structure of the objects they store. The expansion is performed recrusively
to the specified depth. A column can be expanded if it is
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Replace the column index of the frame with the provided sequence of column keys. The columns of the frame are assigned keys according to the current order, or in a non-deterministic way, if the current column index is not ordered.
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Replace the row index of the frame with ordinarilly generated integers starting from zero. The rows of the frame are assigned index according to the current order, or in a non-deterministic way, if the current row index is not ordered.
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Full Usage:
FrameExtensions.IndexRowsUsing(frame, f)
Parameters:
Frame<'R, 'C>
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Source data frame whose row index are to be replaced.
f : Func<ObjectSeries<'C>, 'R2>
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A function from row (as object series) to new row key value
Returns: Frame<'R2, 'C>
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Replace the row index of the frame with a sequence of row keys generated using a function invoked on each row.
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Replace the row index of the frame with the provided sequence of row keys. The rows of the frame are assigned keys according to the current order, or in a non-deterministic way, if the current row index is not ordered.
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Given a data frame whose row index has two levels, create a series whose keys are the unique first level keys, and whose values are those corresponding frames selected from the original data.
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Given a data frame whose row index has two levels, create a series whose keys are the unique results of the keyselector projection, and whose values are those corresponding frames selected from the original data. |
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Align the existing data to a specified collection of row keys. Values in the data frame that do not match any new key are dropped, new keys (that were not in the original data frame) are assigned missing values.
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Returns a data frame that contains the same data as the input, but whose columns are an ordered series. This allows using operations that are only available on indexed series such as alignment and inexact lookup.
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Returns a data frame that contains the same data as the input, but whose rows are sorted by some column.
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Returns a data frame that contains the same data as the input, but whose rows are an ordered series. This allows using operations that are only available on indexed series such as alignment and inexact lookup.
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Returns a data frame that contains the same data as the input, but whose rows are sorted by some column.
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Returns a transposed data frame. The rows of the original data frame are used as the columns of the new one (and vice versa). Use this operation if you have a data frame and you mostly need to access its rows as a series (because accessing columns as a series is more efficient).
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Given a series whose values are frames, create a frame resulting from the concatenation of all the frames' rows, with the resulting keys having two levels. This is the inverse operation to nest.
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Fancy accessors
Static members
| Static member |
Description
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Frame operations
Static members
| Static member |
Description
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Full Usage:
FrameExtensions.PivotTable(frame, r, c, op)
Parameters:
Frame<'R, 'C>
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The input data frame to pivot.
r : 'C
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A column key to group on for the resulting row index
c : 'C
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A column key to group on for the resulting col index
op : Func<Frame<'R, 'C>, 'T>
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A function computing a value from the corresponding bucket frame
Returns: Frame<'RNew, 'CNew>
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Creates a new data frame resulting from a 'pivot' operation. Consider a denormalized data frame representing a table: column labels are field names & table values are observations of those fields. pivotTable buckets the rows along two axes, according to the values of the columns `r` and `c`; and then computes a value for the frame of rows that land in each bucket.
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Frame transformations
Static members
| Static member |
Description
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Returns a new data frame containing only the rows that have distinct values in the specified columns. When multiple rows have the same values in those columns, only the first row (in index order) is preserved.
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Input and output
Static members
| Static member |
Description
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Full Usage:
FrameExtensions.SaveCsv(frame, path, keyNames, ?separator, ?culture)
Parameters:
Frame<'R, 'C>
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The input data frame to be saved.
path : string
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Specifies the output file name where the CSV data should be written
keyNames : string seq
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Specifies the CSV headers for row key (or keys, for multi-level index)
?separator : char
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Specify the column separator in the file (the default is `\t` for TSV files and `,` for CSV files)
?culture : CultureInfo
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Specify the `CultureInfo` object used for formatting numerical data
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Save data frame to a CSV file or to a `Stream`. When calling the operation, you can specify whether you want to save the row keys or not (and headers for the keys) and you can also specify the separator (use `\t` for writing TSV files). When specifying file name ending with `.tsv`, the `\t` separator is used automatically.
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Full Usage:
FrameExtensions.SaveCsv(frame, path, ?includeRowKeys, ?keyNames, ?separator, ?culture)
Parameters:
Frame<'R, 'C>
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The input data frame to be saved.
path : string
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Specifies the output file name where the CSV data should be written
?includeRowKeys : bool
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When set to `true`, the row key is also written to the output file
?keyNames : string
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Can be used to specify the CSV headers for row key (or keys, for multi-level index)
?separator : char
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Specify the column separator in the file (the default is `\t` for TSV files and `,` for CSV files)
?culture : CultureInfo
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Specify the `CultureInfo` object used for formatting numerical data
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Save data frame to a CSV file or to a `Stream`. When calling the operation, you can specify whether you want to save the row keys or not (and headers for the keys) and you can also specify the separator (use `\t` for writing TSV files). When specifying file name ending with `.tsv`, the `\t` separator is used automatically.
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Full Usage:
FrameExtensions.SaveCsv(frame, writer, ?includeRowKeys, ?keyNames, ?separator, ?culture)
Parameters:
Frame<'R, 'C>
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The input data frame to be saved.
writer : TextWriter
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Specifies the text writer to which the CSV data should be written
?includeRowKeys : bool
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When set to `true`, the row key is also written to the output file
?keyNames : string
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Can be used to specify the CSV headers for row key (or keys, for multi-level index)
?separator : char
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Specify the column separator in the file (the default is `\t` for TSV files and `,` for CSV files)
?culture : CultureInfo
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Specify the `CultureInfo` object used for formatting numerical data
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Save data frame to a CSV file or to a `Stream`. When calling the operation, you can specify whether you want to save the row keys or not (and headers for the keys) and you can also specify the separator (use `\t` for writing TSV files). When specifying file name ending with `.tsv`, the `\t` separator is used automatically.
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Full Usage:
FrameExtensions.SaveJson(frame, path, ?orient)
Parameters:
Frame<'R, 'C>
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The input data frame to serialize.
path : string
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The output file path.
?orient : string
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Controls the JSON layout (see ToJson).
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Save the data frame as a JSON file at the specified path.
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Full Usage:
FrameExtensions.SaveJson(frame, writer, ?orient)
Parameters:
Frame<'R, 'C>
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The input data frame to serialize.
writer : TextWriter
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The TextWriter to write JSON to.
?orient : string
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Controls the JSON layout (see ToJson).
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Save the data frame as JSON to the specified
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Returns the data of the frame as a .NET `DataTable` object. The column keys are automatically converted to strings that are used as column names. The row index is turned into an additional column with the specified name (the function takes the name as a sequence to support hierarchical keys, but typically you can write just `frame.ToDataTable(["KeyName"])`.
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Full Usage:
FrameExtensions.ToJson(frame, ?orient)
Parameters:
Frame<'R, 'C>
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The input data frame to serialize.
?orient : string
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Controls the JSON layout. Allowed values:
"columns" (default) — column-major {"col":{"row":v}};
"index" — row-major {"row":{"col":v}};
"records" — array of row objects [{"col":v}].
Returns: string
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Serialize the data frame to a JSON string.
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Missing values
Static members
| Static member |
Description
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Creates a new data frame that drops those columns that are empty for each row. The resulting data frame has the same number of rows, but may have fewer columns (or no columns at all).
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Creates a new data frame that contains only those rows that are empty for each column. The resulting data frame has the same number of columns, but may have fewer rows (or no rows at all).
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Creates a new data frame that contains only those columns of the original data frame that are _dense_, meaning that they have a value for each row. The resulting data frame has the same number of rows, but may have fewer columns (or no columns at all).
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Creates a new data frame that contains only those rows of the original data frame that are _dense_, meaning that they have a value for each column. The resulting data frame has the same number of columns, but may have fewer rows (or no rows at all).
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Full Usage:
FrameExtensions.FillMissing(frame, f)
Parameters:
Frame<'TRowKey, 'TColumnKey>
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An input data frame that is to be filled
f : Func<Series<'TRowKey, 'T>, 'TRowKey, 'T>
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A function that takes a series Series<R, T> together with a key K in the series and generates a value to be used in a place where the original series contains a missing value.
Returns: Frame<'TRowKey, 'TColumnKey>
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Fill missing values in the frame using the specified function. The specified function is called with all series and keys for which the frame does not contain value and the result of the call is used in place of the missing value. The operation is only applied to columns (series) that contain values of the same type as the return type of the provided filling function. The operation does not attempt to convert between numeric values (so a series containing `float` will not be converted to a series of `int`).
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Full Usage:
FrameExtensions.FillMissing(frame, direction)
Parameters:
Frame<'TRowKey, 'TColumnKey>
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An input data frame that is to be filled
direction : Direction
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Specifies the direction used when searching for the nearest available value. `Backward` means that we want to look for the first value with a smaller key while `Forward` searches for the nearest greater key.
Returns: Frame<'TRowKey, 'TColumnKey>
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Fill missing values in the data frame with the nearest available value (using the specified direction). Note that the frame may still contain missing values after call to this function (e.g. if the first value is not available and we attempt to fill series with previous values). This operation can only be used on ordered frames.
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Fill missing values of a given type in the frame with a constant value. The operation is only applied to columns (series) that contain values of the same type as the provided filling value. The operation does not attempt to convert between numeric values (so a series containing `float` will not be converted to a series of `int`).
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