Class DataFrame (0.2.0)

Two-dimensional, size-mutable, potentially heterogeneous tabular data.

Data structure also contains labeled axes (rows and columns). Arithmetic operations align on both row and column labels. Can be thought of as a dict-like container for Series objects. The primary pandas data structure.

Return a list representing the axes of the DataFrame.

It has the row axis labels and column axis labels as the only members. They are returned in that order.

Examples

 df = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})
df.axes
[RangeIndex(start=0, stop=2, step=1), Index(['col1', 'col2'],
dtype='object')] 

The column labels of the DataFrame.

Return the dtypes in the DataFrame.

This returns a Series with the data type of each column. The result's index is the original DataFrame's columns. Columns with mixed types aren't supported yet in BigQuery DataFrames.

Indicates whether Series/DataFrame is empty.

True if Series/DataFrame is entirely empty (no items), meaning any of the axes are of length 0.

Purely integer-location based indexing for selection by position.

.iloc[] is primarily integer position based (from 0 to length-1 of the axis), but may also be used with a boolean array.

Allowed inputs are:

• Not supported yetAn integer, e.g. 5 .
• Not supported yetA list or array of integers, e.g. [4, 3, 0] .
• A slice object with ints, e.g. 1:7 .
• Not supported yetA boolean array.
• Not supported yetA callable function with one argument (the calling Series or DataFrame) that returns valid output for indexing (one of the above). This is useful in method chains, when you don't have a reference to the calling object, but would like to base your selection on some value.
• Not supported yetA tuple of row and column indexes. The tuple elements consist of one of the above inputs, e.g. (0, 1) .

.iloc will raise IndexError if a requested indexer is out-of-bounds, except slice indexers which allow out-of-bounds indexing (this conforms with python/numpy slice semantics).

The index (row labels) of the DataFrame.

The index of a DataFrame is a series of labels that identify each row. The labels can be integers, strings, or any other hashable type. The index is used for label-based access and alignment, and can be accessed or modified using this attribute.

Access a group of rows and columns by label(s) or a boolean array.

.loc[] is primarily label based, but may also be used with a boolean array.

Allowed inputs are:

• A single label, e.g. 5 or 'a' , (note that 5 is interpreted as a label of the index, and neveras an integer position along the index).
• A list of labels, e.g. ['a', 'b', 'c'] .
• A boolean series of the same length as the axis being sliced, e.g. [True, False, True] .
• An alignable Index. The index of the returned selection will be the input.
• Not supported yetAn alignable boolean Series. The index of the key will be aligned before masking.
• Not supported yetA slice object with labels, e.g. 'a':'f' . Note: contrary to usual python slices, boththe start and the stop are included.
• Not supported yetA callable function with one argument (the calling Series or DataFrame) that returns valid output for indexing (one of the above).

Return an int representing the number of axes / array dimensions.

BigQuery job metadata for the most recent query.

Return a tuple representing the dimensionality of the DataFrame.

Return an int representing the number of elements in this object.

Compiles this DataFrame's expression tree to SQL.

Return the values of DataFrame in the form of a NumPy array.

Used to support numpy ufuncs. See: https://numpy.org/doc/stable/reference/ufuncs.html

Gets the specified column(s) from the DataFrame.

Converts a DataFrame to a string. Calls compute.

Only represents the first <xref uid="bigframes.options">bigframes.options</xref>.display.max_rows .

Modify or insert a column into the DataFrame.

Note: This does notmodify the original table the DataFrame was derived from.

Return a Series/DataFrame with absolute numeric value of each element.

This function only applies to elements that are all numeric.

Get addition of DataFrame and other, element-wise (binary operator + ).

Equivalent to dataframe + other . With reverse version, radd .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Prefix labels with string prefix .

For Series, the row labels are prefixed. For DataFrame, the column labels are prefixed.

Suffix labels with string suffix .

For Series, the row labels are suffixed. For DataFrame, the column labels are suffixed.

Aggregate using one or more operations over the specified axis.

Aggregate using one or more operations over the specified axis.

Return whether all elements are True, potentially over an axis.

Returns True unless there at least one element within a Series or along a DataFrame axis that is False or equivalent (e.g. zero or empty).

Return whether any element is True, potentially over an axis.

Returns False unless there is at least one element within a series or along a Dataframe axis that is True or equivalent (e.g. non-zero or non-empty).

Apply a function to a Dataframe elementwise.

This method applies a function that accepts and returns a scalar to every element of a DataFrame.

Assign new columns to a DataFrame.

Returns a new object with all original columns in addition to new ones. Existing columns that are re-assigned will be overwritten.

Cast a pandas object to a specified dtype dtype .

Make a copy of this object's indices and data.

A new object will be created with a copy of the calling object's data and indices. Modifications to the data or indices of the copy will not be reflected in the original object.

Count non-NA cells for each column or row.

The values None , NaN , NaT , and optionally numpy.inf (depending on pandas.options.mode.use_inf_as_na ) are considered NA.

Return cumulative maximum over a DataFrame axis.

Returns a DataFrame of the same size containing the cumulative maximum.

Return cumulative minimum over a DataFrame axis.

Returns a DataFrame of the same size containing the cumulative minimum.

Return cumulative product over a DataFrame axis.

Returns a DataFrame of the same size containing the cumulative product.

Return cumulative sum over a DataFrame axis.

Returns a DataFrame of the same size containing the cumulative sum.

Generate descriptive statistics.

Descriptive statistics include those that summarize the central tendency, dispersion and shape of a dataset's distribution, excluding NaN values.

Only supports numeric columns.

Get floating division of DataFrame and other, element-wise (binary operator / ).

Equivalent to dataframe / other . With reverse version, rtruediv .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Get floating division of DataFrame and other, element-wise (binary operator / ).

Equivalent to dataframe / other . With reverse version, rtruediv .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Drop specified labels from columns.

Remove columns by directly specifying column names.

Return DataFrame with duplicate rows removed.

Considering certain columns is optional. Indexes, including time indexes are ignored.

Return DataFrame with requested index / column level(s) removed.

Remove missing values.

Return boolean Series denoting duplicate rows.

Considering certain columns is optional.

Get equal to of DataFrame and other, element-wise (binary operator eq ).

Among flexible wrappers ( eq , ne , le , lt , ge , gt ) to comparison operators.

Equivalent to == , != , <= , < , >= , > with support to choose axis (rows or columns) and level for comparison.

Get integer division of DataFrame and other, element-wise (binary operator // ).

Equivalent to dataframe // other . With reverse version, rfloordiv .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Get 'greater than or equal to' of DataFrame and other, element-wise (binary operator >= ).

Among flexible wrappers ( eq , ne , le , lt , ge , gt ) to comparison operators.

Equivalent to == , != , <= , < , >= , > with support to choose axis (rows or columns) and level for comparison.

Get item from object for given key (ex: DataFrame column).

Returns default value if not found.

Group DataFrame by columns.

A groupby operation involves some combination of splitting the object, applying a function, and combining the results. This can be used to group large amounts of data and compute operations on these groups.

Get 'greater than' of DataFrame and other, element-wise (binary operator > ).

Among flexible wrappers ( eq , ne , le , lt , ge , gt ) to comparison operators.

Equivalent to == , != , <= , < , >= , > with support to choose axis (rows or columns) and level for comparison.

Return the first n rows.

This function returns the first n rows for the object based on position. It is useful for quickly testing if your object has the right type of data in it.

Not yet supportedFor negative values of n , this function returns all rows except the last |n| rows, equivalent to df[:n] .

If n is larger than the number of rows, this function returns all rows.

Detect missing values.

Return a boolean same-sized object indicating if the values are NA. NA values get mapped to True values. Everything else gets mapped to False values. Characters such as empty strings '' or numpy.inf are not considered NA values.

Detect missing values.

Return a boolean same-sized object indicating if the values are NA. NA values get mapped to True values. Everything else gets mapped to False values. Characters such as empty strings '' or numpy.inf are not considered NA values.

Join columns of another DataFrame.

Join columns with other DataFrame on index

Get 'less than or equal to' of dataframe and other, element-wise (binary operator <= ).

Among flexible wrappers ( eq , ne , le , lt , ge , gt ) to comparison operators.

Equivalent to == , != , <= , < , >= , > with support to choose axis (rows or columns) and level for comparison.

Get 'less than' of DataFrame and other, element-wise (binary operator < ).

Among flexible wrappers ( eq , ne , le , lt , ge , gt ) to comparison operators.

Equivalent to == , != , <= , < , >= , > with support to choose axis (rows or columns) and level for comparison.

Apply a function to a Dataframe elementwise.

This method applies a function that accepts and returns a scalar to every element of a DataFrame.

Return the maximum of the values over the requested axis.

If you want the index of the maximum, use idxmax . This is the equivalent of the numpy.ndarray method argmax .

Return the mean of the values over the requested axis.

Return the median of the values over the requested axis.

Merge DataFrame objects with a database-style join.

The join is done on columns or indexes. If joining columns on columns, the DataFrame indexes will be ignored . Otherwise if joining indexes on indexes or indexes on a column or columns, the index will be passed on. When performing a cross merge, no column specifications to merge on are allowed.

Return the minimum of the values over the requested axis.

If you want the index of the minimum, use idxmin . This is the equivalent of the numpy.ndarray method argmin .

Get modulo of DataFrame and other, element-wise (binary operator % ).

Equivalent to dataframe % other . With reverse version, rmod .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Get multiplication of DataFrame and other, element-wise (binary operator * ).

Equivalent to dataframe * other . With reverse version, rmul .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Get multiplication of DataFrame and other, element-wise (binary operator * ).

Equivalent to dataframe * other . With reverse version, rmul .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Get not equal to of DataFrame and other, element-wise (binary operator ne ).

Among flexible wrappers ( eq , ne , le , lt , ge , gt ) to comparison operators.

Equivalent to == , != , <= , < , >= , > with support to choose axis (rows or columns) and level for comparison.

Detect existing (non-missing) values.

Return a boolean same-sized object indicating if the values are not NA. Non-missing values get mapped to True. Characters such as empty strings '' or numpy.inf are not considered NA values. NA values get mapped to False values.

Detect existing (non-missing) values.

Return a boolean same-sized object indicating if the values are not NA. Non-missing values get mapped to True. Characters such as empty strings '' or numpy.inf are not considered NA values. NA values get mapped to False values.

Count number of distinct elements in specified axis.

Return reshaped DataFrame organized by given index / column values.

Reshape data (produce a "pivot" table) based on column values. Uses unique values from specified index / columns to form axes of the resulting DataFrame. This function does not support data aggregation, multiple values will result in a MultiIndex in the columns.

Return the product of the values over the requested axis.

Return the product of the values over the requested axis.

Get addition of DataFrame and other, element-wise (binary operator + ).

Equivalent to dataframe + other . With reverse version, radd .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Compute numerical data ranks (1 through n) along axis.

By default, equal values are assigned a rank that is the average of the ranks of those values.

Get floating division of DataFrame and other, element-wise (binary operator / ).

Equivalent to other / dataframe . With reverse version, truediv .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Rename columns.

Dict values must be unique (1-to-1). Labels not contained in a dict will be left as-is. Extra labels listed don't throw an error.

Set the name of the axis for the index.

Rearrange index levels using input order. May not drop or duplicate levels.

Reset the index.

Reset the index of the DataFrame, and use the default one instead.

Get integer division of DataFrame and other, element-wise (binary operator // ).

Equivalent to other // dataframe . With reverse version, rfloordiv .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Get modulo of DataFrame and other, element-wise (binary operator % ).

Equivalent to other % dataframe . With reverse version, mod .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Get multiplication of DataFrame and other, element-wise (binary operator * ).

Equivalent to dataframe * other . With reverse version, rmul .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Get subtraction of DataFrame and other, element-wise (binary operator - ).

Equivalent to other - dataframe . With reverse version, sub .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Get floating division of DataFrame and other, element-wise (binary operator / ).

Equivalent to other / dataframe . With reverse version, truediv .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Return a random sample of items from an axis of object.

You can use random_state for reproducibility.

Set the DataFrame index using existing columns.

Set the DataFrame index (row labels) using one existing column. The index can replace the existing index.

Shift index by desired number of periods.

Shifts the index without realigning the data.

Sort object by labels (along an axis).

Sort by the values along row axis.

Return sample standard deviation over requested axis.

Normalized by N-1 by default.

Get subtraction of DataFrame and other, element-wise (binary operator - ).

Equivalent to dataframe - other . With reverse version, rsub .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Get subtraction of DataFrame and other, element-wise (binary operator - ).

Equivalent to dataframe - other . With reverse version, rsub .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Return the sum of the values over the requested axis.

This is equivalent to the method numpy.sum .

Return the last n rows.

This function returns last n rows from the object based on position. It is useful for quickly verifying data, for example, after sorting or appending rows.

For negative values of n , this function returns all rows except the first |n| rows, equivalent to df[|n|:] .

If n is larger than the number of rows, this function returns all rows.

Write object to a comma-separated values (csv) file on Cloud Storage.

Write a DataFrame to a BigQuery table.

Convert the object to a JSON string, written to Cloud Storage.

Note NaN's and None will be converted to null and datetime objects will be converted to UNIX timestamps.

Convert the DataFrame to a NumPy array.

Write DataFrame to pandas DataFrame.

Write a DataFrame to the binary Parquet format.

This function writes the dataframe as a parquet file <https://parquet.apache.org/> _ to Cloud Storage.

Get floating division of DataFrame and other, element-wise (binary operator / ).

Equivalent to dataframe / other . With reverse version, rtruediv .

Among flexible wrappers ( add , sub , mul , div , mod , pow ) to arithmetic operators: + , - , * , / , // , % , ** .

Return a Series containing counts of unique rows in the DataFrame.

Return unbiased variance over requested axis.

Normalized by N-1 by default.