cyberpandas 1.1.1

Manipulate JSON-like data with NumPy-like idioms.

pandera supports built-in python types or strings representing the legal pandas datatypes, or pandera’s DataType:

Quick Start Code Example of the pandera library.

import pandas as pd
import numpy as np
from matplotlib import pyplot as plt

#using numpy's randint to generate some data
df1 = pd.DataFrame(np.random.randint(0,100,size=(10, 2)), columns=list('XY'))
df2 = pd.DataFrame(np.random.randint(0,100,size=(10, 2)), columns=list('XY'))
df3 = pd.DataFrame(np.random.randint(0,100,size=(10, 2)), columns=list('XY'))

df1.head(), df2.head(), df3.head()

(    X   Y
 0  82  32
 1  79  13
 2  87  19
 3   6  73
 4   1  38,
     X   Y
 0  47  62
 1  41   0
 2  98  78
 3  63  83
 4  31  59,
     X   Y
 0  57  25
 1  49  27
 2   9  29
 3  93  75
 4  23  80)

# Get handle of first figure to pass to other plot() calls as ax
ax =  df1.plot(color="red", figsize=(10,5))
df2.plot(ax=ax, color="orange", figsize=(10,5))
df3.plot(ax=ax, color="green", figsize=(10,5))

# Note: subsequent plots need to happen in the same notebook cell.

<AxesSubplot:>

Finance plotting

Download market data from Yahoo! Finance API

In this example Python code, we use requests to fetch data from the EIA.gov website and json from the Python standard library to parse the json data. Next, we load the daily prices into a Pandas DataFrame and format the date column and set it as the index. Finally, we use Pandas .plot() to create a chart saving it as a png image.

A pandas-based library to visualize and compare datasets.

Draw NetworkX graphs with Altair