The Python Pandas data box's str column is built into the method detailed __python

Original link: http://www.datastudy.cc/to/27
In the process of using the dataframe of the pandas framework, if you need to handle some character strings, such as determining whether a column contains some keywords, whether a column has a character length of less than 3, and so on, it can be much easier to handle if you master the method built into the STR column.
Let's take a look at the details of what the Str-band method of the series class is.
1, Cat ()   Stitching string          Example:          >>> series ([' A ',  ' B ',  ' C ']). Str.cat ([' A ',  ' B ',  ' C '], sep= '), ')         0 a,a         1  b,b         2 c,c          dtype: object         >>> series ([' A ',  ') B ',  ' C ']). Str.cat (sep= ', ')          ' a,b,c '          >>> series ([' A ',  ' B ']). Str.cat ([' x ',  ' y '], [' 1 ',  ') 2 ']], sep= ', ')         0    a,x,1          1    b,y,2          dtyPe: object 2, Split ()   Shard string         >>> import  numpy,pandas;         >>> s = pandas. Series ([' A_b_c ',  ' c_d_e ', numpy.nan,  ' f_g_h '])          >>> s.str.split ('_')         0    [a,  B, C]         1    [c, d, e]         2           NaN         3    [f, g, h]          dtype: object         >> > s.str.split (' _ ',  -1)         0    [a ,  b,&nbsP;C]         1    [c, d, e]          2          nan          3    [F, G, H]          dtype: object         >>>  S.str.split (' _ ',  0)         0    [a, b,  C]         1    [c, d, e]          2          nan         3    [F, G, H]          dtype: object          >>>  s.str.split (' _ ',  1)         0    [a, b_c]          1    [c, d_e]          2         nan          3    [f, g_h]         dtype:  Object         >>> s.str.split (' _ ',  2)          0    [A, B, C]          1    [c, d, e]          2          nan          3    [F, G, H]         dtype:  Object &NBsp;       >>> s.str.split (' _ ',  3)          0    [A, B, C]          1    [c, d, e]         2           nan          3    [F, G, H]         dtype:  Object 3, Get () gets the string at the specified location         >>> s.str.get (0)          0      a          1      c         2     nan         3       f   &nbsP;     dtype: object         >>>  s.str.get (1)         0      _          1      _          2    nan         3       _         dtype: object          >>> s.str.get (2)         0       b         1       d         2    nan          3      g          Dtype: object 4, join ()   concatenation of each character with the point string, not commonly used         >> > s.str.join ("!")         0    a!_!b!_!c         1    c!_!d!_!e          2          nan          3    f!_!g!_!h          dtype: object         >>> s.str.join ("?")         0    a?_?b?_?c          1    c?_?d?_?e         2           nan          3    F?_?g?_?h         dtype: object          >>> s.str.join (".")         0     A._.B._.C         1    C._.D._.E         2           NaN         3    f._.g._.h          dtype: object 5, contains () contains an expression          >>> s.str.contains (' d ')         0     False         1     true          2      nan          3&nbsP;   false         dtype: object 6, replace ()          >>> s.str.replace ("_",  ".")         0    A.B.C          1    C.D.E         2       nan         3    f.g.h         dtype: object 7, repeat () repeat          >>> s.str.repeat (3)         0     a_b_ca_b_ca_b_c         1    c_d_ Ec_d_ec_d_e         2              &nbSp;  nan         3    f_g_hf_g_hf_g_h         dtype: object 8, pad () padded >>> s.str.pad (10,  fillchar= "?") 0    ????? A_b_c 1    ????? C_d_e 2           nan 3    ????? F_g_h dtype: object >>> >>> s.str.pad (10, side= "right",  fillchar= "?") 0    a_b_c?????