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Updated docs
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pandas/io/parsers.py

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@@ -132,10 +132,10 @@ class ParserWarning(Warning):
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Note: A fast-path exists for iso8601-formatted dates.
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infer_datetime_format : boolean, default False
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If parse_dates is enabled and this flag is set, pandas will attempt to
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infer the format of the datetime strings in the columns, and if it can be
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inferred, switch to a faster method of parsing them. In some cases this
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can increase the parsing speed by ~5-10x.
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If True and parse_dates is enabled, pandas will attempt to infer the format
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of the datetime strings in the columns, and if it can be inferred, switch
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to a faster method of parsing them. In some cases this can increase the
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parsing speed by ~5-10x.
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keep_date_col : boolean, default False
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If True and parse_dates specifies combining multiple columns then
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keep the original columns.

pandas/tseries/tools.py

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@@ -231,8 +231,10 @@ def to_datetime(arg, errors='raise', dayfirst=False, yearfirst=False,
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unit : unit of the arg (D,s,ms,us,ns) denote the unit in epoch
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(e.g. a unix timestamp), which is an integer/float number.
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infer_datetime_format : boolean, default False
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If no `format` is given, try to infer the format based on the first
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datetime string. Provides a large speed-up in many cases.
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If True and no `format` is given, attempt to infer the format of the
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datetime strings, and if it can be inferred, switch to a faster
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method of parsing them. In some cases this can increase the parsing
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speed by ~5-10x.
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Returns
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-------

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