I do not quite understand why this is required though. The data then has to be unnested two times. ) ) %>% # convert data type readr :: type_convert () ) ) %>% # 2nd time to nest the single list in each cell? unnest ( cols = names (. Lp_df = lp_wider %>% # 1st time unnest to release the 2-dimension list? unnest ( cols = names (. Therefore, only the parts wrapped inside the LPS is the “actual” data I need.

TYPE_CODE, DIST_CODE and INFO_CODE are data dictionary to store the ID used to encode data. The tree structure of the XML is in the below form:ĭEPARTMENT, GENERATION_DATE and LINK are metadata. The XML data file looks like something below: Unluckily, the dataset is available in XML format only. Currently I need to find data about the restaurant licenses in Hong Kong, and FEHD provides an open dataset. However, sometimes the government discloses open data in XML format only. Tidyr (in tidyverse) provides functions unnest_wider and unnest_longer to transform XML data into dataframe quickly, using the same ideology of pivot_wider and pivot_longer in dplyr.

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