# pandas.Series.to_hdf

`Series.``to_hdf`(path_or_buf, key, **kwargs)

  activate the HDFStore

  Parameters:

  path_or_buf : the path (string) or HDFStore object

  key : string

  > indentifier for the group in the store

  mode : optional, {‘a’, ‘w’, ‘r’, ‘r+’}, default ‘a’

  > `'r'`

  >   Read-only; no data can be modified.

  > `'w'`

  >   Write; a new file is created (an existing file with the same name would be deleted).

  > `'a'`

  >   Append; an existing file is opened for reading and writing, and if the file does not exist it is created.

  > `'r+'`

  >   It is similar to `'a'`, but the file must already exist.

  format : ‘fixed(f)|table(t)’, default is ‘fixed’

  > fixed(f) : Fixed format

  >   Fast writing/reading. Not-appendable, nor searchable

  > table(t) : Table format

  >   Write as a PyTables Table structure which may perform worse but allow more flexible operations like searching / selecting subsets of the data

  append : boolean, default False

  > For Table formats, append the input data to the existing

  complevel : int, 1-9, default 0

  > If a complib is specified compression will be applied where possible

  complib : {‘zlib’, ‘bzip2’, ‘lzo’, ‘blosc’, None}, default None

  > If complevel is > 0 apply compression to objects written in the store wherever possible

  fletcher32 : bool, default False

  > If applying compression use the fletcher32 checksum

  dropna : boolean, default False.

  > If true, ALL nan rows will not be written to store.