def describe(self, strings=True, virtual=True, selection=None):
import pandas as pd<EOL>N = len(self)<EOL>columns = {}<EOL>for feature in self.get_column_names(strings=strings, virtual=virtual)[:]:<EOL><INDENT>dtype = str(self.dtype(feature)) if self.dtype(feature) != str else '<STR_LIT:str>'<EOL>if self.dtype(feature) == str_type or self.dtype(feature).kind in ['<STR_LIT:S>', '<STR_LIT>', '<STR_LIT:O>']:<EOL><INDENT>count = self.count(feature, selection=selection, delay=True)<EOL>self.execute()<EOL>count = count.get()<EOL>columns[feature] = ((dtype, count, N-count, '<STR_LIT>', '<STR_LIT>', '<STR_LIT>', '<STR_LIT>'))<EOL><DEDENT>else:<EOL><INDENT>count = self.count(feature, selection=selection, delay=True)<EOL>mean = self.mean(feature, selection=selection, delay=True)<EOL>std = self.std(feature, selection=selection, delay=True)<EOL>minmax = self.minmax(feature, selection=selection, delay=True)<EOL>self.execute()<EOL>count, mean, std, minmax = count.get(), mean.get(), std.get(), minmax.get()<EOL>count = int(count)<EOL>columns[feature] = ((dtype, count, N-count, mean, std, minmax[<NUM_LIT:0>], minmax[<NUM_LIT:1>]))<EOL><DEDENT><DEDENT>return pd.DataFrame(data=columns, index=['<STR_LIT>', '<STR_LIT:count>', '<STR_LIT>', '<STR_LIT>', '<STR_LIT>', '<STR_LIT>', '<STR_LIT>'])<EOL>
Give a description of the DataFrame.

        >>> import vaex
        >>> df = vaex.example()[['x', 'y', 'z']]
        >>> df.describe()
                         x          y          z
        dtype      float64    float64    float64
        count       330000     330000     330000
        missing          0          0          0
        mean    -0.0671315 -0.0535899  0.0169582
        std        7.31746    7.78605    5.05521
        min       -128.294   -71.5524   -44.3342
        max        271.366    146.466    50.7185
        >>> df.describe(selection=df.x > 0)
                           x         y          z
        dtype        float64   float64    float64
        count         164060    164060     164060
        missing       165940    165940     165940
        mean         5.13572 -0.486786 -0.0868073
        std          5.18701   7.61621    5.02831
        min      1.51635e-05  -71.5524   -44.3342
        max          271.366   78.0724    40.2191

        :param bool strings: Describe string columns or not
        :param bool virtual: Describe virtual columns or not
        :param selection: Optional selection to use.
        :return: Pandas dataframe