 pandas: powerful Python data analysis toolkit - 0.13.1Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide,0 码力 | 1219 页 | 4.81 MB | 1 年前3 pandas: powerful Python data analysis toolkit - 0.13.1Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide,0 码力 | 1219 页 | 4.81 MB | 1 年前3
 pandas: powerful Python data analysis toolkit - 0.14.0Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide,0 码力 | 1349 页 | 7.67 MB | 1 年前3 pandas: powerful Python data analysis toolkit - 0.14.0Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide,0 码力 | 1349 页 | 7.67 MB | 1 年前3
 pandas: powerful Python data analysis toolkit - 0.17.0Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, occurrences of pattern/regex in the Series/Index with some other string. Equivalent to str.replace() or re.sub(). Parameters pat : string Character sequence or regular expression repl : string Replacement0 码力 | 1787 页 | 10.76 MB | 1 年前3 pandas: powerful Python data analysis toolkit - 0.17.0Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, occurrences of pattern/regex in the Series/Index with some other string. Equivalent to str.replace() or re.sub(). Parameters pat : string Character sequence or regular expression repl : string Replacement0 码力 | 1787 页 | 10.76 MB | 1 年前3
 pandas: powerful Python data analysis toolkit - 0.15Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide,0 码力 | 1579 页 | 9.15 MB | 1 年前3 pandas: powerful Python data analysis toolkit - 0.15Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide,0 码力 | 1579 页 | 9.15 MB | 1 年前3
 pandas: powerful Python data analysis toolkit - 0.15.1Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide,0 码力 | 1557 页 | 9.10 MB | 1 年前3 pandas: powerful Python data analysis toolkit - 0.15.1Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide, Notes •Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. •Regular expressions will only substitute on strings, meaning you cannot provide,0 码力 | 1557 页 | 9.10 MB | 1 年前3
 pandas: powerful Python data analysis toolkit - 1.3.2string The replace method can also take a callable as replacement. It is called on every pat using re.sub(). The callable should expect one positional argument (a regex object) and return a string. 556 replace('col_heading', '')\ .replace('row_heading', '') import re html = re.sub(r'col[0-9]+', lambda x: x.group().replace('col', 'c'), html) html = re.sub(r'row[0-9]+', lambda x: x.group().replace('row', 'r'), html) Notes • Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. • Regular expressions will only substitute on strings, meaning you cannot provide0 码力 | 3509 页 | 14.01 MB | 1 年前3 pandas: powerful Python data analysis toolkit - 1.3.2string The replace method can also take a callable as replacement. It is called on every pat using re.sub(). The callable should expect one positional argument (a regex object) and return a string. 556 replace('col_heading', '')\ .replace('row_heading', '') import re html = re.sub(r'col[0-9]+', lambda x: x.group().replace('col', 'c'), html) html = re.sub(r'row[0-9]+', lambda x: x.group().replace('row', 'r'), html) Notes • Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. • Regular expressions will only substitute on strings, meaning you cannot provide0 码力 | 3509 页 | 14.01 MB | 1 年前3
 pandas: powerful Python data analysis toolkit - 1.3.3string The replace method can also take a callable as replacement. It is called on every pat using re.sub(). The callable should expect one positional argument (a regex object) and return a string. 2.9 replace('col_heading', '')\ .replace('row_heading', '') import re html = re.sub(r'col[0-9]+', lambda x: x.group().replace('col', 'c'), html) html = re.sub(r'row[0-9]+', lambda x: x.group().replace('row', 'r'), html) Notes • Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. • Regular expressions will only substitute on strings, meaning you cannot provide0 码力 | 3603 页 | 14.65 MB | 1 年前3 pandas: powerful Python data analysis toolkit - 1.3.3string The replace method can also take a callable as replacement. It is called on every pat using re.sub(). The callable should expect one positional argument (a regex object) and return a string. 2.9 replace('col_heading', '')\ .replace('row_heading', '') import re html = re.sub(r'col[0-9]+', lambda x: x.group().replace('col', 'c'), html) html = re.sub(r'row[0-9]+', lambda x: x.group().replace('row', 'r'), html) Notes • Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. • Regular expressions will only substitute on strings, meaning you cannot provide0 码力 | 3603 页 | 14.65 MB | 1 年前3
 pandas: powerful Python data analysis toolkit - 1.3.4string The replace method can also take a callable as replacement. It is called on every pat using re.sub(). The callable should expect one positional argument (a regex object) and return a string. 582 replace('col_heading', '')\ .replace('row_heading', '') import re html = re.sub(r'col[0-9]+', lambda x: x.group().replace('col', 'c'), html) html = re.sub(r'row[0-9]+', lambda x: x.group().replace('row', 'r'), html) Notes • Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. • Regular expressions will only substitute on strings, meaning you cannot provide0 码力 | 3605 页 | 14.68 MB | 1 年前3 pandas: powerful Python data analysis toolkit - 1.3.4string The replace method can also take a callable as replacement. It is called on every pat using re.sub(). The callable should expect one positional argument (a regex object) and return a string. 582 replace('col_heading', '')\ .replace('row_heading', '') import re html = re.sub(r'col[0-9]+', lambda x: x.group().replace('col', 'c'), html) html = re.sub(r'row[0-9]+', lambda x: x.group().replace('row', 'r'), html) Notes • Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. • Regular expressions will only substitute on strings, meaning you cannot provide0 码力 | 3605 页 | 14.68 MB | 1 年前3
 pandas: powerful Python data analysis toolkit - 0.20.3method, see here. • Series.str.replace() now accepts a callable, as replacement, which is passed to re.sub (GH15055) • Series.str.replace() now accepts a compiled regular expression as a pattern (GH15446) object The replace method can also take a callable as replacement. It is called on every pat using re.sub(). The callable should expect one positional argument (a regex object) and return a string. New Notes • Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. • Regular expressions will only substitute on strings, meaning you cannot provide0 码力 | 2045 页 | 9.18 MB | 1 年前3 pandas: powerful Python data analysis toolkit - 0.20.3method, see here. • Series.str.replace() now accepts a callable, as replacement, which is passed to re.sub (GH15055) • Series.str.replace() now accepts a compiled regular expression as a pattern (GH15446) object The replace method can also take a callable as replacement. It is called on every pat using re.sub(). The callable should expect one positional argument (a regex object) and return a string. New Notes • Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. • Regular expressions will only substitute on strings, meaning you cannot provide0 码力 | 2045 页 | 9.18 MB | 1 年前3
 pandas: powerful Python data analysis toolkit - 0.20.2Release 0.20.2 • Series.str.replace() now accepts a callable, as replacement, which is passed to re.sub (GH15055) • Series.str.replace() now accepts a compiled regular expression as a pattern (GH15446) object The replace method can also take a callable as replacement. It is called on every pat using re.sub(). The callable should expect one positional argument (a regex object) and return a string. New Notes • Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. • Regular expressions will only substitute on strings, meaning you cannot provide0 码力 | 1907 页 | 7.83 MB | 1 年前3 pandas: powerful Python data analysis toolkit - 0.20.2Release 0.20.2 • Series.str.replace() now accepts a callable, as replacement, which is passed to re.sub (GH15055) • Series.str.replace() now accepts a compiled regular expression as a pattern (GH15446) object The replace method can also take a callable as replacement. It is called on every pat using re.sub(). The callable should expect one positional argument (a regex object) and return a string. New Notes • Regex substitution is performed under the hood with re.sub. The rules for substitution for re.sub are the same. • Regular expressions will only substitute on strings, meaning you cannot provide0 码力 | 1907 页 | 7.83 MB | 1 年前3
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