In [47]: s3.str.replace('^.a|dog', 'XX-XX ', case=False) Out[47]: 0 A 1 B 2 C 3 XX-XX ba 4 XX-XX ca 5 6 7 XX-XX BA 8 XX-XX 9 XX-XX t dtype: string Some caution must be taken to keep regular powerful Python data analysis toolkit, Release 1.1.1 (continued from previous page) 3 XX-XX ba 4 XX-XX ca 5 6 7 XX-XX BA 8 XX-XX 9 XX-XX t dtype: string Including a flags argument when calling replace analysis toolkit, Release 1.1.1 (continued from previous page) Out[95]: -1 -z-- 0 aaab 1 bbbd 2 c-ca 3 dddc 4 -e-- dtype: string If using join='right' on a list-like of others that contains different

object In [24]: s3.str.replace('^.a|dog', 'XX-XX ', case=False) Out[24]: 0 A 1 B 2 C 3 XX-XX ba 4 XX-XX ca 5 6 NaN 7 XX-XX BA 8 XX-XX 9 XX-XX t dtype: object Some caution must be taken to keep regular expressions IGNORECASE) In [39]: s3.str.replace(regex_pat, 'XX-XX ') Out[39]: 0 A 1 B 2 C 3 XX-XX ba 4 XX-XX ca 5 6 NaN 7 XX-XX BA 8 XX-XX 9 XX-XX t dtype: object Including a flags argument when calling replace object In [56]: u Out[56]: 1 b 3 d 0 a 2 c dtype: object In [57]: s.str.cat(u) Out[57]: 0 ab 1 bd 2 ca 3 dc dtype: object In [58]: s.str.cat(u, join='left') Out[58]: 0 aa 1 bb 2 cc 3 dd dtype: object

str.replace("^.a|dog", "XX-XX ", case=False, regex=True) Out[47]: 0 A 1 B 2 C 3 XX-XX ba 4 XX-XX ca 5 6 (continues on next page) 2.2. Guides 591 pandas: powerful Python data analysis toolkit In [59]: s3.str.replace(regex_pat, "XX-XX ", regex=True) Out[59]: 0 A 1 B 2 C 3 XX-XX ba 4 XX-XX ca 5 6 7 XX-XX BA 8 XX-XX 9 XX-XX t dtype: string Including a flags argument when calling replace [96]: s.str.cat([v, u, u.to_numpy()], join="outer", na_rep="-") Out[96]: -1 -z-- 0 aaab 1 bbbd 2 c-ca 3 dddc 4 -e-- dtype: string If using join='right' on a list-like of others that contains different

sep='|', chunksize=4) In [191]: reader Out[191]: ca0> In [192]: for chunk in reader: .....: print(chunk) .....: Unnamed: 0 0 1 2 3 0 0 0.469112 -0 In [47]: s3.str.replace('^.a|dog', 'XX-XX ', case=False) Out[47]: 0 A 1 B 2 C 3 XX-XX ba 4 XX-XX ca 5 6 7 XX-XX BA 8 XX-XX 9 XX-XX t dtype: string Some caution must be taken to keep regular powerful Python data analysis toolkit, Release 1.1.0 (continued from previous page) 3 XX-XX ba 4 XX-XX ca 5 6 7 XX-XX BA 8 XX-XX 9 XX-XX t dtype: string Including a flags argument when calling replace

str.replace("^.a|dog", "XX-XX ", case=False, regex=True) Out[47]: 0 A 1 B 2 C 3 XX-XX ba 4 XX-XX ca 5 6 7 XX-XX BA 8 XX-XX 9 XX-XX t dtype: string Warning: Some caution must be taken when In [59]: s3.str.replace(regex_pat, "XX-XX ", regex=True) Out[59]: 0 A 1 B 2 C 3 XX-XX ba 4 XX-XX ca 5 6 7 XX-XX BA 8 XX-XX 9 XX-XX t dtype: string Including a flags argument when calling replace [92]: s.str.cat([v, u, u.to_numpy()], join="outer", na_rep="-") Out[92]: -1 -z-- 0 aaab 1 bbbd 2 c-ca 3 dddc 4 -e-- dtype: string If using join='right' on a list-like of others that contains different

\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\Out[24]: ˓→ 0 A 1 B 2 C 3 XX-XX ba 4 XX-XX ca 5 6 NaN 7 XX-XX BA 8 XX-XX (continues on next page) 490 Chapter 4. User Guide pandas: powerful IGNORECASE) In [39]: s3.str.replace(regex_pat, 'XX-XX ') Out[39]: 0 A 1 B 2 C 3 XX-XX ba 4 XX-XX ca 5 6 NaN 7 XX-XX BA 8 XX-XX 9 XX-XX t dtype: object Including a flags argument when calling replace \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\Out[57]: ˓→ 0 ab 1 bd 2 ca 3 dc dtype: object In [58]: s.str.cat(u, join='left') \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\

hist(normed=True, alpha=0.2) Out[6]: ca8d0> In [7]: s.plot(kind=’kde’) Out[7]: ca8d0> 1.10. v0.8.0 (June 29, 2012) 79 pandas: powerful Python [203]: s3.str.replace(’^.a|dog’, ’XX-XX ’, case=False) Out[203]: 0 A 1 B 2 C 3 XX-XX ba 4 XX-XX ca 5 6 NaN 7 XX-XX BA 8 XX-XX 9 XX-XX t dtype: object 9.9.2 Extracting Substrings The method extract from the World Bank’s servers: In [3]: dat = wb.download(indicator=’NY.GDP.PCAP.KD’, country=[’US’, ’CA’, ’MX’], start=2005, end=2008) In [4]: print(dat) NY.GDP.PCAP.KD country year Canada 2008 36005.5004978584

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\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\Out[24]: ˓→ 0 A 1 B 2 C 3 XX-XX ba 4 XX-XX ca 5 6 NaN 7 XX-XX BA 8 XX-XX (continues on next page) 490 Chapter 4. User Guide pandas: powerful IGNORECASE) In [39]: s3.str.replace(regex_pat, 'XX-XX ') Out[39]: 0 A 1 B 2 C 3 XX-XX ba 4 XX-XX ca 5 6 NaN 7 XX-XX BA 8 XX-XX 9 XX-XX t dtype: object Including a flags argument when calling replace \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\Out[57]: ˓→ 0 ab 1 bd 2 ca 3 dc dtype: object In [58]: s.str.cat(u, join='left') \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\

\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\Out[6]: ca20> In [7]: s.plot(kind='kde') \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\Out[7]: ˓→ca20> 352 Chapter 1. What’s New pandas: powerful Python data analysis toolkit, Release 0.20.3 See the \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\Out[24]: ˓→ 0 A 1 B 2 C 3 XX-XX ba 4 XX-XX ca 5 6 NaN 7 XX-XX BA 8 XX-XX 9 XX-XX t dtype: object Some caution must be taken to keep regular