Dataset Column Details¶

First, we'll initialize a client with our server credentials and store it in the variable dai.

In [1]:

import driverlessai

dai = driverlessai.Client(address='http://mr-dl26:12345', username='py', password='py')

import driverlessai dai = driverlessai.Client(address='http://mr-dl26:12345', username='py', password='py')

In [5]:

dai.datasets.list()

dai.datasets.list()

Out[5]:

    | Type    | Key                                  | Name
----+---------+--------------------------------------+--------------
  0 | Dataset | 20bc1880-efb7-11eb-82af-0242c0a8fe02 | iris.csv.zip

In [7]:

dataset = dai.datasets.list()[0]

dataset = dai.datasets.get("20bc1880-efb7-11eb-82af-0242c0a8fe02")

dataset = dai.datasets.list()[0] dataset = dai.datasets.get("20bc1880-efb7-11eb-82af-0242c0a8fe02")

column_summaries

In [9]:

dataset.column_summaries()

dataset.column_summaries()

Out[9]:

<<C1 Summary>, <C2 Summary>, <C3 Summary>, <C4 Summary>, <C5 Summary>>

In [18]:

C1_summary = dataset.column_summaries()["C1"]

C1_summary = dataset.column_summaries()["C1"]

In [19]:

print(C1_summary)

print(C1_summary)

--- C1 ---

 4.3|███████
    |█████████████████
    |██████████
    |████████████████████
    |████████████
    |███████████████████
    |█████████████
    |████
    |████
 7.9|████

Data Type: real
Logical Types: []
Datetime Format: 
Count: 150
Missing: 0
Mean: 5.84
SD: 0.828
Min: 4.3
Max: 7.9
Unique: 35
Freq: 10

In [20]:

C5_summary.sd

C5_summary.sd

Out[20]:

0.8280661279778637