otp.Operation.str.ilike#

ilike(pattern)#

Check if the value is case insensitive matched with SQL-like pattern.

Parameters

pattern (str or symbol parameter (_SymbolParamColumn)) –

Pattern to match the value with. The pattern can contain usual text characters and two special ones:

  • % represents zero or more characters

  • _ represents a single character

Use backslash \ character to escape these special characters.

Returns

True if the match was successful, False otherwise. Note that boolean Operation is converted to float if added as a column.

Return type

Operation

Examples

Use % character to specify any number of characters:

data = otp.Ticks(X=['a', 'ab', 'Ab', 'b_'])
data['LIKE'] = data['X'].str.ilike('a%')
df = otp.run(data)
print(df)

                     Time   X  LIKE
0 2003-12-01 00:00:00.000   a   1.0
1 2003-12-01 00:00:00.001  ab   1.0
2 2003-12-01 00:00:00.002  Ab   1.0
3 2003-12-01 00:00:00.003  b_   0.0

Use _ special character to specify a single character:

data = otp.Ticks(X=['a', 'ab', 'Ab', 'b_'])
data['LIKE'] = data['X'].str.ilike('a_')
df = otp.run(data)
print(df)

                     Time   X  LIKE
0 2003-12-01 00:00:00.000   a   0.0
1 2003-12-01 00:00:00.001  ab   1.0
2 2003-12-01 00:00:00.002  Ab   1.0
3 2003-12-01 00:00:00.003  b_   0.0

Use backslash \ character to escape special characters:

data = otp.Ticks(X=['a', 'ab', 'bb', 'b_'])
data['LIKE'] = data['X'].str.ilike(r'b\_')
df = otp.run(data)
print(df)

                     Time   X  LIKE
0 2003-12-01 00:00:00.000   a   0.0
1 2003-12-01 00:00:00.001  ab   0.0
2 2003-12-01 00:00:00.002  bb   0.0
3 2003-12-01 00:00:00.003  b_   1.0

This function can be used to filter out ticks:

data = otp.Ticks(X=['a', 'ab', 'Ab', 'b_'])
data = data.where(data['X'].str.ilike('a%'))
df = otp.run(data)
print(df)

                     Time   X
0 2003-12-01 00:00:00.000   a
1 2003-12-01 00:00:00.001  ab
2 2003-12-01 00:00:00.002  Ab

pattern can only be a constant expression, like string or symbol parameter:

data = otp.Ticks(X=['a', 'ab', 'A', 'b_'])
data['LIKE'] = data['X'].str.ilike(data.Symbol['PATTERN', str])
df = otp.run(data, symbols=otp.Tick(SYMBOL_NAME='COMMON::AAPL', PATTERN='_'))['COMMON::AAPL']
print(df)

                     Time   X  LIKE
0 2003-12-01 00:00:00.000   a   1.0
1 2003-12-01 00:00:00.001  ab   0.0
2 2003-12-01 00:00:00.002   A   1.0
3 2003-12-01 00:00:00.003  b_   0.0