@@ -1170,8 +1170,12 @@ def put(
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complevel : int, 0-9, default None
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Specifies a compression level for data.
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A value of 0 or None disables compression.
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- min_itemsize : int, dict, or None
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- Dict of columns that specify minimum str sizes.
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+ min_itemsize : int, dict, or None, default None
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+ Refers to the minimum size for string columns in bytes.
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+ When the format = 'table'.
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+ Since this specifies the byte length after encoding,
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+ multi-byte characters need to be calculated using
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+ their encoded byte length rather than character count.
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nan_rep : str
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Str to use as str nan representation.
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data_columns : list of columns or True, default None
@@ -1203,6 +1207,9 @@ def put(
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>>> df = pd.DataFrame([[1, 2], [3, 4]], columns=["A", "B"])
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>>> store = pd.HDFStore("store.h5", "w") # doctest: +SKIP
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>>> store.put("data", df) # doctest: +SKIP
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+
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+ >>> The word 'hello' = 5 bytes
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+ >>> Japanese character "勉" = 2 bytes
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"""
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if format is None :
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format = get_option ("io.hdf.default_format" ) or "fixed"
@@ -1330,8 +1337,12 @@ def append(
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A value of 0 or None disables compression.
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columns : default None
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This parameter is currently not accepted, try data_columns.
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- min_itemsize : int, dict, or None
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- Dict of columns that specify minimum str sizes.
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+ min_itemsize : int, dict, or None, default None
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+ Refers to the minimum size for string columns in bytes.
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+ When the format = 'table'.
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+ Since this specifies the byte length after encoding,
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+ multi-byte characters need to be calculated using
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+ their encoded byte length rather than character count.
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nan_rep : str
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Str to use as str nan representation.
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chunksize : int or None
@@ -1377,6 +1388,9 @@ def append(
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1 3 4
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0 5 6
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1 7 8
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+
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+ >>> The word 'hello' = 5 bytes
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+ >>> Japanese character "勉" = 2 bytes
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"""
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if columns is not None :
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raise TypeError (
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