bigframes.pandas.DataFrame.describe

DataFrame.describe(include: None | Literal['all'] = None) → DataFrame

Generate descriptive statistics.

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

Parameters:

include ("all" or None, optional) – If “all”: All columns of the input will be included in the output. If None: The result will include all numeric columns.

Note

Percentile values are approximates only.

Note

For numeric data, the result’s index will include count, mean, std, min, max as well as lower, 50 and upper percentiles. By default the lower percentile is 25 and the upper percentile is 75. The 50 percentile is the same as the median.

Examples:

>>> import bigframes.pandas as bpd
>>> df = bpd.DataFrame({"A": [3, 1, 2], "B": [0, 2, 8], "C": ["cat", "cat", "dog"]})
>>> df
   A  B    C
0  3  0  cat
1  1  2  cat
2  2  8  dog

[3 rows x 3 columns]

>>> df.describe()
         A         B
count  3.0       3.0
mean   2.0  3.333333
std    1.0  4.163332
min    1.0       0.0
25%    1.0       0.0
50%    2.0       2.0
75%    3.0       8.0
max    3.0       8.0

[8 rows x 2 columns]

Using describe with include = “all”:

>>> df.describe(include="all")
            A         B     C
count     3.0       3.0     3
nunique  <NA>      <NA>     2
mean      2.0  3.333333  <NA>
std       1.0  4.163332  <NA>
min       1.0       0.0  <NA>
25%       1.0       0.0  <NA>
50%       2.0       2.0  <NA>
75%       3.0       8.0  <NA>
max       3.0       8.0  <NA>

[9 rows x 3 columns]

Returns:

Summary statistics of the Series or Dataframe provided.

Return type:

bigframes.pandas.DataFrame

Raises:

ValueError – If unsupported include type is provided.