EmptyDataError. Sounds Familiar? Then read stick with me for some tips to avoid any form of error when loading your CSV files using Pandas… After reading, you will definitely not get this error anymore.
The first step of data cleaning/wrangling is loading the file and then establishing a connection via the path of a file. There are different types of delimited files like tab-separated file, comma-separated file, multi-character delimited file etc. The delimitations indicate how the data is to be separated within columns whether through comma, tab or semicolon etc. The most commonly used files are tab-separated and comma-separated files.
Data wrangling and cleaning accounts for about 50 to 70% of the Data analytics professionals’ time within the whole ML pipeline. The first step is to import the file to a Pandas DataFrame. However, this step constitutes the most encountered errors. People often get stuck in this particular step and come across errors like
EmptyDataError: No columns to parse from file
The common errors occur, mainly, due to :
· Wrong file delimiters mentioned.
· File path not formed properly.
· Wrong syntax or separator used to specify the file path.
· Wrong file directory mentioned.
· File Connection not formed.
Data analytics professionals cannot afford more time being drained into an already time-consuming step. While loading the file, certain important steps must be followed which will save time and cut through the hassle of scouring through a plethora of information to find the solution to your specific problem. Therefore, I have laid out some steps to avoid any error while importing and loading a data file using pandas DataFrame.
Reading and importing the CSV file is not so simple as one may surmise. Here are some tips which must be kept in mind once you start loading your file to build your Machine Learning model.
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