rnalysis.filtering.DESeqFilter.describe

DESeqFilter.describe(percentiles: float | List[float] = (0.01, 0.25, 0.5, 0.75, 0.99)) → DataFrame

Generate descriptive statistics that summarize the central tendency, dispersion and shape of the dataset’s distribution, excluding NaN values. For more information see the documentation of pandas.DataFrame.describe.

Parameters:

percentiles (list-like of floats (default=(0.01, 0.25, 0.5, 0.75, 0.99))) – The percentiles to include in the output. All should fall between 0 and 1. The default is [.25, .5, .75], which returns the 25th, 50th, and 75th percentiles.

Returns:

Summary statistics of the dataset.

Return type:

Series or DataFrame

Examples:

>>> from rnalysis import filtering
>>> import numpy as np
>>> counts = filtering.Filter('tests/test_files/counted.csv')
>>> counts.describe()
              cond1         cond2         cond3         cond4
count     22.000000     22.000000     22.000000     22.000000
mean    2515.590909   2209.227273   4230.227273   3099.818182
std     4820.512674   4134.948493   7635.832664   5520.394522
min        0.000000      0.000000      0.000000      0.000000
1%         0.000000      0.000000      0.000000      0.000000
25%        6.000000      6.250000      1.250000      0.250000
50%       57.500000     52.500000     23.500000     21.000000
75%     2637.000000   2479.000000   6030.500000   4669.750000
99%    15054.950000  12714.290000  21955.390000  15603.510000
max    15056.000000  12746.000000  22027.000000  15639.000000

>>> # show the deciles (10%, 20%, 30%... 90%) of the columns
>>> counts.describe(percentiles=np.arange(0.1, 1, 0.1))
              cond1         cond2         cond3         cond4
count     22.000000     22.000000     22.000000     22.000000
mean    2515.590909   2209.227273   4230.227273   3099.818182
std     4820.512674   4134.948493   7635.832664   5520.394522
min        0.000000      0.000000      0.000000      0.000000
10%        0.000000      0.200000      0.000000      0.000000
20%        1.400000      3.200000      1.000000      0.000000
30%       15.000000     15.700000      2.600000      1.000000
40%       28.400000     26.800000     14.000000      9.000000
50%       57.500000     52.500000     23.500000     21.000000
60%       82.000000    106.800000     44.000000     33.000000
70%      484.200000    395.500000    305.000000    302.500000
80%     3398.600000   3172.600000   7981.400000   6213.000000
90%     8722.100000   7941.800000  16449.500000  12129.900000
max    15056.000000  12746.000000  22027.000000  15639.000000