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docs: code samples for drop and fillna (#284)
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‎third_party/bigframes_vendored/pandas/core/frame.py

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Original file line numberDiff line numberDiff line change
@@ -869,6 +869,97 @@ def drop(
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Remove columns by directly specifying column names.
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**Examples:**
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>>> import bigframes.pandas as bpd
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>>> bpd.options.display.progress_bar = None
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>>> df = bpd.DataFrame(np.arange(12).reshape(3, 4),
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... columns=['A', 'B', 'C', 'D'])
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>>> df
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A B C D
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0 0 1 2 3
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1 4 5 6 7
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2 8 9 10 11
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<BLANKLINE>
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[3 rows x 4 columns]
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Drop columns:
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>>> df.drop(['B', 'C'], axis=1)
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A D
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0 0 3
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1 4 7
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2 8 11
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<BLANKLINE>
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[3 rows x 2 columns]
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>>> df.drop(columns=['B', 'C'])
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A D
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0 0 3
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1 4 7
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2 8 11
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<BLANKLINE>
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[3 rows x 2 columns]
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Drop a row by index:
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>>> df.drop([0, 1])
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A B C D
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2 8 9 10 11
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<BLANKLINE>
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[1 rows x 4 columns]
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Drop columns and/or rows of MultiIndex DataFrame:
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>>> import pandas as pd
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>>> midx = pd.MultiIndex(levels=[['llama', 'cow', 'falcon'],
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... ['speed', 'weight', 'length']],
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... codes=[[0, 0, 0, 1, 1, 1, 2, 2, 2],
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... [0, 1, 2, 0, 1, 2, 0, 1, 2]])
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>>> df = bpd.DataFrame(index=midx, columns=['big', 'small'],
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... data=[[45, 30], [200, 100], [1.5, 1], [30, 20],
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... [250, 150], [1.5, 0.8], [320, 250],
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... [1, 0.8], [0.3, 0.2]])
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>>> df
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big small
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llama speed 45.0 30.0
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weight 200.0 100.0
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length 1.5 1.0
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cow speed 30.0 20.0
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weight 250.0 150.0
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length 1.5 0.8
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falcon speed 320.0 250.0
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weight 1.0 0.8
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length 0.3 0.2
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<BLANKLINE>
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[9 rows x 2 columns]
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Drop a specific index and column combination from the MultiIndex
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DataFrame, i.e., drop the index ``'cow'`` and column ``'small'``:
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>>> df.drop(index='cow', columns='small')
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big
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llama speed 45.0
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weight 200.0
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length 1.5
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falcon speed 320.0
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weight 1.0
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length 0.3
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<BLANKLINE>
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[6 rows x 1 columns]
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>>> df.drop(index='length', level=1)
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big small
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llama speed 45.0 30.0
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weight 200.0 100.0
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cow speed 30.0 20.0
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weight 250.0 150.0
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falcon speed 320.0 250.0
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weight 1.0 0.8
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<BLANKLINE>
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[6 rows x 2 columns]
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Args:
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labels:
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Index or column labels to drop.
@@ -4343,6 +4434,56 @@ def fillna(self, value):
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"""
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Fill NA/NaN values using the specified method.
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**Examples:**
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>>> import bigframes.pandas as bpd
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>>> bpd.options.display.progress_bar = None
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>>> df = bpd.DataFrame([[np.nan, 2, np.nan, 0],
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... [3, 4, np.nan, 1],
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... [np.nan, np.nan, np.nan, np.nan],
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... [np.nan, 3, np.nan, 4]],
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... columns=list("ABCD")).astype("Float64")
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>>> df
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A B C D
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0 <NA> 2.0 <NA> 0.0
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1 3.0 4.0 <NA> 1.0
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2 <NA> <NA> <NA> <NA>
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3 <NA> 3.0 <NA> 4.0
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<BLANKLINE>
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[4 rows x 4 columns]
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Replace all NA elements with 0s.
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>>> df.fillna(0)
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A B C D
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0 0.0 2.0 0.0 0.0
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1 3.0 4.0 0.0 1.0
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2 0.0 0.0 0.0 0.0
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3 0.0 3.0 0.0 4.0
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<BLANKLINE>
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[4 rows x 4 columns]
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You can use fill values from another DataFrame:
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>>> df_fill = bpd.DataFrame(np.arange(12).reshape(3, 4),
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... columns=['A', 'B', 'C', 'D'])
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>>> df_fill
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A B C D
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0 0 1 2 3
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1 4 5 6 7
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2 8 9 10 11
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<BLANKLINE>
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[3 rows x 4 columns]
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>>> df.fillna(df_fill)
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A B C D
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0 0.0 2.0 2.0 0.0
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1 3.0 4.0 6.0 1.0
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2 8.0 9.0 10.0 11.0
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3 <NA> 3.0 <NA> 4.0
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<BLANKLINE>
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[4 rows x 4 columns]
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Args:
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value (scalar, Series):
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Value to use to fill holes (e.g. 0), alternately a

‎third_party/bigframes_vendored/pandas/core/series.py

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Original file line numberDiff line numberDiff line change
@@ -1062,6 +1062,55 @@ def drop(
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When using a multi-index, labels on different levels can be removed
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by specifying the level.
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**Examples:**
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>>> import bigframes.pandas as bpd
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>>> bpd.options.display.progress_bar = None
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>>> s = bpd.Series(data=np.arange(3), index=['A', 'B', 'C'])
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>>> s
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A 0
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B 1
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C 2
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dtype: Int64
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Drop labels B and C:
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>>> s.drop(labels=['B', 'C'])
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A 0
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dtype: Int64
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Drop 2nd level label in MultiIndex Series:
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>>> import pandas as pd
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>>> midx = pd.MultiIndex(levels=[['llama', 'cow', 'falcon'],
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... ['speed', 'weight', 'length']],
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... codes=[[0, 0, 0, 1, 1, 1, 2, 2, 2],
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... [0, 1, 2, 0, 1, 2, 0, 1, 2]])
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>>> s = bpd.Series([45, 200, 1.2, 30, 250, 1.5, 320, 1, 0.3],
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... index=midx)
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>>> s
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llama speed 45.0
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weight 200.0
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length 1.2
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cow speed 30.0
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weight 250.0
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length 1.5
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falcon speed 320.0
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weight 1.0
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length 0.3
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dtype: Float64
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>>> s.drop(labels='weight', level=1)
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llama speed 45.0
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length 1.2
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cow speed 30.0
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length 1.5
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falcon speed 320.0
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length 0.3
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dtype: Float64
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Args:
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labels (single label or list-like):
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Index labels to drop.
@@ -1193,6 +1242,38 @@ def fillna(
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"""
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Fill NA/NaN values using the specified method.
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**Examples:**
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>>> import bigframes.pandas as bpd
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>>> bpd.options.display.progress_bar = None
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>>> s = bpd.Series([np.nan, 2, np.nan, -1])
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>>> s
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0 <NA>
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1 2.0
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2 <NA>
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3 -1.0
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dtype: Float64
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Replace all NA elements with 0s.
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>>> s.fillna(0)
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0 0.0
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1 2.0
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2 0.0
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3 -1.0
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dtype: Float64
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You can use fill values from another Series:
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>>> s_fill = bpd.Series([11, 22, 33])
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>>> s.fillna(s_fill)
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0 11.0
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1 2.0
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2 33.0
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3 -1.0
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dtype: Float64
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Args:
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value (scalar, dict, Series, or DataFrame, default None):
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Value to use to fill holes (e.g. 0).

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