I don't know enough of the parquet options to be sure that all partitioned files have the same metadata as the others (I'm producing these files using pandas). Note: My platform does not have the same interface as. Would you please help to convert it in Dataframe I know how to convert in the RDD: DF.map(lambda x: float(x.price) But, I am trying to do all the conversion in the Dataframe. Adding parsedates to pd.readcsv will cause Pandas to automatically convert strings that.astype (.) is deprecated and will raise in a future version. DF.price DF.price.astype(float) Panda like script did not work. I actually got a warning with this : FutureWarning: casting datetime64 ns values to int64 with. You should use pd.Series.astype (float) or pd.tonumeric as described in other answers. DFDF.price float(DF.price)) did not work. I know that I can use LabelEncocder from sklearn.preprocessing and then use OHE and it works well, but in that case. I read the answers to similar questions and then opened scikit-learn documentations, but how you can see scikit-learn authors doesn't have issues with spaces in strings. I try to check the data types, they look the same, Unfortunately I don't have a way to investigate all the data in each category types in the 64 files (I have more 250 columns and several of them are categorical). 7 Answers Sorted by: 82 NOTE: pd.convertobjects has now been deprecated. ValueError: could not convert string to float: 'New York'. Maybe remove this from the data string before you. In order to do so i would recommend altering the string in order to keep exclusively numbers. Unfortunately, I cannot share the data that lead to that error because they are privileged, but it would be greatly appreciated if someone can give me an idea of where to begin investigate. At the bottom of your error, you will see ValueError: could not convert string to float: b'', which is likely because you are trying to import a string in place of a float (in this case, it looks literally like the string of multiple asterisks: which could be a column-header delimiter). The only part from the string python could actually convert is 44. So even if you provide a string and itâs a valid value for the float function, itâll convert it into a floating number. I have to note that I was successful before using a randomly half sample of this same data partitioned in 32 parts. When I try to replicate this behavior, the corr() method works OK but spits out a warning (shown below) that warns that the ignoring of non-numeric columns will be removed in the future. How Does float() Work in Python The float() function type casts any right and acceptable data types into a float number. Distributed.worker - WARNING - Compute FailedÄ®xception: ValueError("could not convert string to float: ''")
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