Wenn ich einen Scala-Absatz mit einem DataFrame habe, kann ich diesen mit Python teilen und verwenden. (Wie ich es verstehe, verwendet pyspark py4j)

Ich habe es versucht:

Scala Absatz:

x.printSchema
z.put("xtable", x )

Python Absatz:

%pyspark

import numpy as np
import pandas as pd

import matplotlib.pyplot as plt
import seaborn as sns

the_data = z.get("xtable")

print the_data

sns.set()
g = sns.PairGrid(data=the_data,
                 x_vars=dependent_var,
                 y_vars=sensor_measure_columns_names +  operational_settings_columns_names,
                 hue="UnitNumber", size=3, aspect=2.5)
g = g.map(plt.plot, alpha=0.5)
g = g.set(xlim=(300,0))
g = g.add_legend()

Error

Traceback (most recent call last):
  File "/tmp/zeppelin_pyspark.py", line 222, in <module>
    eval(compiledCode)
  File "<string>", line 15, in <module>
  File "/usr/local/lib/python2.7/dist-packages/seaborn/axisgrid.py", line 1223, in __init__
    hue_names = utils.categorical_order(data[hue], hue_order)
TypeError: 'JavaObject' object has no attribute '__getitem__'

Lösung

%pyspark

import numpy as np
import pandas as pd

import matplotlib.pyplot as plt
import seaborn as sns

import StringIO
def show(p):
    img = StringIO.StringIO()
    p.savefig(img, format='svg')
    img.seek(0)
    print "%html <div style='width:600px'>" + img.buf + "</div>"

df = sqlContext.table("fd").select()
df.printSchema
pdf = df.toPandas()

g = sns.pairplot(data=pdf,
                 x_vars=["setting1","setting2"],
                 y_vars=["s4", "s3", 
                         "s9", "s8", 
                         "s13", "s6"],
                 hue="id", aspect=2)
show(g)