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DOC: unify newlines/spacing with substitutions
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pandas/io/formats/info.py

+11-11
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@@ -34,7 +34,7 @@
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frame_max_cols_sub = dedent(
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"""\
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"""
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max_cols : int, optional
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When to switch from the verbose to the truncated output. If the
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DataFrame has more than `max_cols` columns, the truncated output
@@ -44,7 +44,7 @@
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show_counts_sub = dedent(
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"""\
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"""
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show_counts : bool, optional
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Whether to show the non-null counts. By default, this is shown
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only if the DataFrame is smaller than
@@ -54,15 +54,15 @@
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)
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null_counts_sub = dedent(
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"""\
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"""
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null_counts : bool, optional
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.. deprecated:: 1.2.0
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Use show_counts instead."""
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)
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frame_examples_sub = dedent(
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"""\
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"""
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>>> int_values = [1, 2, 3, 4, 5]
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>>> text_values = ['alpha', 'beta', 'gamma', 'delta', 'epsilon']
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>>> float_values = [0.0, 0.25, 0.5, 0.75, 1.0]
@@ -148,7 +148,7 @@
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frame_see_also_sub = dedent(
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"""\
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"""
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DataFrame.describe: Generate descriptive statistics of DataFrame
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columns.
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DataFrame.memory_usage: Memory usage of DataFrame columns."""
@@ -168,7 +168,7 @@
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series_examples_sub = dedent(
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"""\
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"""
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>>> int_values = [1, 2, 3, 4, 5]
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>>> text_values = ['alpha', 'beta', 'gamma', 'delta', 'epsilon']
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>>> s = pd.Series(text_values, index=int_values)
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series_see_also_sub = dedent(
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"""\
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"""
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Series.describe: Generate descriptive statistics of Series.
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Series.memory_usage: Memory usage of Series."""
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)
@@ -280,8 +280,8 @@
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made based in column dtype and number of rows assuming values
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consume the same memory amount for corresponding dtypes. With deep
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memory introspection, a real memory usage calculation is performed
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at the cost of computational resources.
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{show_counts_sub}
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at the cost of computational resources.\
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{show_counts_sub}\
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{null_counts_sub}
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Returns
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This method prints a summary of a {klass} and returns None.
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See Also
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--------
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--------\
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{see_also_sub}
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Examples
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--------
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--------\
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{examples_sub}
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"""
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)

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