pandas.HDFStore.put#

HDFStore.put(key,value,format=None,index=True,append=False,complib=None,complevel=None,min_itemsize=None,nan_rep=None,data_columns=None,encoding=None,errors='strict',track_times=True,dropna=False)[source]#

Store object in HDFStore.

Parameters:

keystr

value{Series, DataFrame}

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

Format to use when storing object in HDFStore. Value can be one of:

'fixed'

Fixed format. Fast writing/reading. Not-appendable, nor searchable.

'table'

Table format. Write as a PyTables Table structure which may performworse but allow more flexible operations like searching / selectingsubsets of the data.

indexbool, default True

Write DataFrame index as a column.

appendbool, default False

This will force Table format, append the input data to the existing.

data_columnslist of columns or True, default None

List of columns to create as data columns, or True to use all columns.Seehere.

encodingstr, default None

Provide an encoding for strings.

track_timesbool, default True

Parameter is propagated to ‘create_table’ method of ‘PyTables’.If set to False it enables to have the same h5 files (same hashes)independent on creation time.

dropnabool, default False, optional

Remove missing values.

Examples

>>>df=pd.DataFrame([[1,2],[3,4]],columns=['A','B'])>>>store=pd.HDFStore("store.h5",'w')>>>store.put('data',df)