Jupyter Notebooks
✎ 8 mos agonotebooks
programming
In addition to wolfram-notebooks, I can now render Jupyter Notebooks on this site! This note briefly explores one.
Exploring Jupyter
This is a Jupyter Notebook that's rendered as HTML within this note. Therefore, the styling of notes permeates through and gets applied to the notebook. For example, these texts are bold, italic, and code.
For now, we'll explore some basic features.
Equations:
Let's take a look into our dataframe:
[1]
from matplotlib import pyplot as plt
import numpy as np
import pandas as pd
# Generate 100 random data points along 3 dimensions
x, y, scale = np.random.randn(3, 100)
fig, ax = plt.subplots()
# Map each onto a scatterplot we'll create with Matplotlib
ax.scatter(x=x, y=y, c=scale, s=np.abs(scale)*500)
ax.set(title="Some random data, created with JupyterLab!")
plt.show()
Plotting Data
Charts are cool. Why not plot one then?
[2]
pd.Series([1, 3, 5, np.nan, 6, 8])0 1.0
1 3.0
2 5.0
3 NaN
4 6.0
5 8.0
dtype: float64[3]
pd.DataFrame(
{
"A": 1.0,
"B": pd.Timestamp("20130102"),
"C": pd.Series(1, index=list(range(4)), dtype="float32"),
"D": np.array([3] * 4, dtype="int32"),
"E": pd.Categorical(["test", "train", "test", "train"]),
"F": "foo",
}
)| A | B | C | D | E | F | |
|---|---|---|---|---|---|---|
| 0 | 1.0 | 2013-01-02 | 1.0 | 3 | test | foo |
| 1 | 1.0 | 2013-01-02 | 1.0 | 3 | train | foo |
| 2 | 1.0 | 2013-01-02 | 1.0 | 3 | test | foo |
| 3 | 1.0 | 2013-01-02 | 1.0 | 3 | train | foo |
[4]
ts = pd.Series(np.random.randn(1000), index=pd.date_range("1/1/2000", periods=1000))
ts = ts.cumsum()
ts.plot()<AxesSubplot:>
｜ jupyter-notebooks