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https://issues.apache.org/jira/browse/SPARK-31600?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-31600.
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Resolution: Invalid
> Error message from DataFrame creation is misleading.
> ----------------------------------------------------
>
> Key: SPARK-31600
> URL: https://issues.apache.org/jira/browse/SPARK-31600
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.4.5
> Environment: DataBricks 6.4, Spark 2.4.5, Scala 2.11
> Reporter: Olexiy Oryeshko
> Priority: Major
>
> *Description:*
> DataFrame creation from pandas.DataFrame fails when one of the features
> contains only NaN values (which is ok).
> However, error message mentions wrong feature as the culprit, which makes it
> hard to find the root cause.
> *How to reproduce:*
>
> {code:java}
> import numpy as np
> import pandas as pd
> df2 = pd.DataFrame({'a': np.array([np.nan, np.nan], dtype=np.object_), 'b':
> [np.nan, 'aaa']})
> display(spark.createDataFrame(df2[['b']])) # Works fine
> spark.createDataFrame(df2) # Raises TypeError.
> {code}
> In the code above, column 'a' is bad. However, the `TypeError` raised in the
> last command mentions feature 'b' as the culprit:
> TypeError: field b: Can not merge type <class 'pyspark.sql.types.DoubleType'>
> and <class 'pyspark.sql.types.StringType'>
>
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