I want to select rows that the values do not start with some str. For example, I have a pandas df
, and I want to select data do not start with t
, a
You can use str.startswith
and negate it.
df[~df['col'].str.startswith('t') &
~df['col'].str.startswith('c')]
col
1 mext1
3 okl1
Or the better option, with multiple characters in a tuple as per @Ted Petrou:
df[~df['col'].str.startswith(('t','c'))]
col
1 mext1
3 okl1
Just another alternative in case you prefer regex:
df1[df1.col.str.contains('^[^tc]')]
option 1
use str.match
and negative look ahead
df[df.col.str.match('^(?![tc])')]
option 2
within query
df.query('col.str[0] not list("tc")')
option 3
numpy
broadcasting
df[(df.col.str[0][:, None] == ['t', 'c']).any(1)]
col
1 mext1
3 okl1
time testing
def ted(df):
return df[~df.col.str.get(0).isin(['t', 'c'])]
def adele(df):
return df[~df['col'].str.startswith(('t','c'))]
def yohanes(df):
return df[df.col.str.contains('^[^tc]')]
def pir1(df):
return df[df.col.str.match('^(?![tc])')]
def pir2(df):
return df.query('col.str[0] not in list("tc")')
def pir3(df):
df[(df.col.str[0][:, None] == ['t', 'c']).any(1)]
functions = pd.Index(['ted', 'adele', 'yohanes', 'pir1', 'pir2', 'pir3'], name='Method')
lengths = pd.Index([10, 100, 1000, 5000, 10000], name='Length')
results = pd.DataFrame(index=lengths, columns=functions)
from string import ascii_lowercase
for i in lengths:
a = np.random.choice(list(ascii_lowercase), i)
df = pd.DataFrame(dict(col=a))
for j in functions:
results.set_value(
i, j,
timeit(
'{}(df)'.format(j),
'from __main__ import df, {}'.format(j),
number=1000
)
)
fig, axes = plt.subplots(3, 1, figsize=(8, 12))
results.plot(ax=axes[0], title='All Methods')
results.drop('pir2', 1).plot(ax=axes[1], title='Drop `pir2`')
results[['ted', 'adele', 'pir3']].plot(ax=axes[2], title='Just the fast ones')
fig.tight_layout()
You can use the apply
method.
Take your question as a example, the code is like this
df[df['col'].apply(lambda x: x[0] not in ['t', 'c'])]
I think apply
is a more general and flexible method.
You can use the str accessor to get string functionality. The get
method can grab a given index of the string.
df[~df.col.str.get(0).isin(['t', 'c'])]
col
1 mext1
3 okl1
Looks like you can use startswith
as well with a tuple (and not a list) of the values you want to exclude.
df[~df.col.str.startswith(('t', 'c'))]