After reading this chapter, the following points have been observed:
- pandas provides powerful methods so that we can read from and write to a variety of data structures and a variety of sources.
- The read_csv method in pandas can be used for reading CSV files, TXT files, and tables. This method has a multitude of arguments in order to specify delimiters, which rows to skip while reading, reading a file in smaller chunks, and so on.
- pandas can be used to read data directly from URLs or S3.
- DataFrames can be converted into JSON and vice versa. JSON can be stored in text files that can be read.
- JSONs have dictionary-like structures that can be nested an infinite number of times. This nested data can be subsetted just like a dictionary with keys.
- Pandas provide methods so that we can read data from the HD5, HTML, SAS, SQL, parquet, feather, and Google BigQuery data formats...