Pandas dataframe to Spark dataframe "Can not merge type error"

Question

I have csv data and created Pandas dataframe using read_csv and forcing all columns as string. Then when I try to create Spark dataframe from the Pandas dataframe, I get the error message below.

from pyspark import SparkContext
from pyspark.sql import SQLContext
from pyspark.sql.types import *
z=pd.read_csv("mydata.csv", dtype=str)
z.info()

<class 'pandas.core.frame.DataFrame'>
Int64Index: 74044003 entries, 0 to 74044002
Data columns (total 12 columns):
primaryid       object
event_dt        object
age             object
age_cod         object
age_grp         object
sex             object
occr_country    object
drug_seq        object
drugname        object
route           object
outc_cod        object
pt              object

q= sqlContext.createDataFrame(z)

File "<stdin>", line 1, in <module>
File "/usr/hdp/2.4.2.0-258/spark/python/pyspark/sql/context.py", line 425, in createDataFrame
rdd, schema = self._createFromLocal(data, schema)
 File "/usr/hdp/2.4.2.0-258/spark/python/pyspark/sql/context.py", line 341, in _createFromLocal
struct = self._inferSchemaFromList(data)
 File "/usr/hdp/2.4.2.0-258/spark/python/pyspark/sql/context.py", line 241, in _inferSchemaFromList
schema = reduce(_merge_type, map(_infer_schema, data))
 File "/usr/hdp/2.4.2.0-258/spark/python/pyspark/sql/types.py", line 862, in _merge_type
for f in a.fields]
 File "/usr/hdp/2.4.2.0-258/spark/python/pyspark/sql/types.py", line 856, in _merge_type
raise TypeError("Can not merge type %s and %s" % (type(a), type(b)))
TypeError: Can not merge type <class 'pyspark.sql.types.DoubleType'> and <class 'pyspark.sql.types.StringType'>

Here is an example. I am downloading public data and creating pandas dataframe but spark does not create spark dataframe from the pandas dataframe.

import pandas as pd
from pyspark import SparkContext
from pyspark.sql import SQLContext
from pyspark.sql.types import *

url ="http://www.nber.org/fda/faers/2016/demo2016q1.csv.zip"

import requests, zipfile, StringIO
r = requests.get(url, stream=True)
z = zipfile.ZipFile(StringIO.StringIO(r.content))
z.extractall()


z=pd.read_csv("demo2016q1.csv") # creates pandas dataframe

Data_Frame = sqlContext.createDataFrame(z)

Answer 1

You could also try to

1. import your data as a pandas dataframe
2. replace the Nans for a string
3. try now to change the pandas df into spark df

df["column"].iloc[np.where(df["column"].isna() == True[0]] = "Nan values"