NotebookConsole
Jupyter Notebook's Console¶
A Jupyter console is an interactive terminal that allows you to execute code, inspect variables, and use shell commands.
It is connected to a Jupyter notebook’s Python kernel, which means that you can access the same variables and functions that are defined in the notebook. This makes it a powerful tool for debugging and testing code, as well as for exploring data interactively.
This notebook provides an example on how to open a Jupyter console in VIM which is connected to the notebook’s kernel. To integrate Vim with a Jupyter Console, it's possible to use the vim-floaterm plugin.
In [11]:
# Cell 1: Import the libraries
import pandas as pd
import numpy as np
In [12]:
# Cell 2: Create a DataFrame with some random data
df = pd.DataFrame(np.random.randint(0, 100, size=(10, 4)), columns=list('ABCD'))
df
Out[12]:
| A | B | C | D | |
|---|---|---|---|---|
| 0 | 0 | 96 | 26 | 16 |
| 1 | 81 | 36 | 42 | 26 |
| 2 | 21 | 42 | 61 | 56 |
| 3 | 81 | 16 | 42 | 6 |
| 4 | 22 | 8 | 42 | 53 |
| 5 | 59 | 48 | 59 | 95 |
| 6 | 82 | 66 | 34 | 3 |
| 7 | 58 | 88 | 16 | 84 |
| 8 | 44 | 31 | 9 | 61 |
| 9 | 90 | 94 | 5 | 27 |
Descriptive statistics¶
In [30]:
# Cell 3: Calculate some statistics on the DataFrame
df.describe(percentiles = [.5])
Out[30]:
| A | B | C | D | |
|---|---|---|---|---|
| count | 10.000000 | 10.000000 | 10.000000 | 10.000000 |
| mean | 53.800000 | 52.500000 | 33.600000 | 42.700000 |
| std | 31.104841 | 32.032102 | 19.431932 | 32.007117 |
| min | 0.000000 | 8.000000 | 5.000000 | 3.000000 |
| 50% | 58.500000 | 45.000000 | 38.000000 | 40.000000 |
| max | 90.000000 | 96.000000 | 61.000000 | 95.000000 |
Correlation matrix¶
In [28]:
df.corr()
Out[28]:
| A | B | C | D | |
|---|---|---|---|---|
| A | 1.000000 | 0.021969 | -0.188388 | -0.245709 |
| B | 0.021969 | 1.000000 | -0.504997 | -0.053591 |
| C | -0.188388 | -0.504997 | 1.000000 | 0.141095 |
| D | -0.245709 | -0.053591 | 0.141095 | 1.000000 |
In [14]:
# Cell 4: Sort the DataFrame by column A
# df.sort_values(by='A')
In [ ]: