pandas dataframe filter

In [3]: df[df['ids'].str.contains("ball")]  # removes all rows where 'ball' not in row['ids']
Out[3]:
     ids  vals
0  aball     1
1  bball     2
3  fball     4

df = pd.DataFrame(np.array(([1, 2, 3], [4, 5, 6])),
...                   index=['mouse', 'rabbit'],
...                   columns=['one', 'two', 'three'])
>>> df
        one  two  three
mouse     1    2      3
rabbit    4    5      6

# select columns by name
df.filter(items=['one', 'three'])
         one  three
mouse     1      3
rabbit    4      6

# select columns by regular expression
df.filter(regex='e$', axis=1)
         one  three
mouse     1      3
rabbit    4      6

# select rows containing 'bbi'
df.filter(like='bbi', axis=0)
         one  two  three
rabbit    4    5      6

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# filter rows for year 2002 using  the boolean expression
>gapminder_2002 = gapminder[gapminder['year']==2002]
>print(gapminder_2002.shape)
(142, 6)