匹配 DataFrame 列中的字符串

Question

我有如下测试数据框（原始文件为 60 x 350）

Speci 45 46 47 48 49 50 51
   PP  A  T  A  -  G  G  A
   JJ  G  T  A  -  T  A  G
   KK  A  T  -  A  G  -  A
   LL  A  C  A  A  G  G  A
   MM  G  C  A  A  G  G  G
   NN  C  -  G  T  C  C  T

基本上我想做的是传递一个输入字符串和列名称/编号，如下所示

input string: CAAGGA
ColF (Column from): 46
ColT ( Column To ): 51

并精确匹配每个对应的指定列(From to )并按降序输出最佳匹配如下

Species Matchs
LL  6
MM  5
PP  4

R / Python 我仅用于 ggplots 和基本文件处理的语言，不确定如何遍历数据帧和匹配。

Answer 1

在R中，我们可以写一个函数

test_func <- function(df, ColF, ColT, input_string) {
   #Split input string at every character
   str <- strsplit(input_string, "")[[1]]
   #Create a sequence between column numbers that match
   cols <- do.call(seq, as.list(match(c(ColF, ColT), names(df))))
   #Count number of exact matches in each row
   vals <- apply(df[cols], 1, function(x) sum(x == str))
   #Sort them in descending order
   ord_vals <- order(vals, decreasing = TRUE)
   #Display it
   data.frame(Species = df$Speci[ord_vals], vals[ord_vals])
}

input_string =  "CAAGGA"
ColF = 46
ColT = 51

test_func(df, ColF, ColT, input_string)
#  Species value
#1      LL     6
#2      MM     5
#3      PP     4
#4      KK     3
#5      JJ     1
#6      NN     0

数据

df <- structure(list(Speci = structure(c(6L, 1L, 2L, 3L, 4L, 5L), .Label = c("JJ", 
"KK", "LL", "MM", "NN", "PP"), class = "factor"), `45` = structure(c(1L, 
3L, 1L, 1L, 3L, 2L), .Label = c("A", "C", "G"), class = "factor"), 
`46` = structure(c(3L, 3L, 3L, 2L, 2L, 1L), .Label = c("-", 
"C", "T"), class = "factor"), `47` = structure(c(2L, 2L, 
1L, 2L, 2L, 3L), .Label = c("-", "A", "G"), class = "factor"), 
`48` = structure(c(1L, 1L, 2L, 2L, 2L, 3L), .Label = c("-", 
"A", "T"), class = "factor"), `49` = structure(c(2L, 3L, 
2L, 2L, 2L, 1L), .Label = c("C", "G", "T"), class = "factor"), 
`50` = structure(c(4L, 2L, 1L, 4L, 4L, 3L), .Label = c("-", 
"A", "C", "G"), class = "factor"), `51` = structure(c(1L, 
2L, 1L, 1L, 2L, 3L), .Label = c("A", "G", "T"), class = "factor")), 
class = "data.frame", row.names = c(NA, -6L))

Answer 2

一个pandas解决方案：

s = (df.loc[:, "46":"51"]
     .groupby(df.index)
     .apply(lambda x: (x==np.array(list("CAAGGA"))).sum(axis=1))
     ).reset_index(drop=True)

print (df.merge(s.rename("best match"), left_index=True, right_index=True).sort_values("best match",ascending=False))

#
  Speci 45 46 47 48 49 50 51  best match
3    LL  A  C  A  A  G  G  A           6
4    MM  G  C  A  A  G  G  G           5
0    PP  A  T  A  -  G  G  A           4
2    KK  A  T  -  A  G  -  A           3
1    JJ  G  T  A  -  T  A  G           1
5    NN  C  -  G  T  C  C  T           0

或列表理解：

df["match"] = [(row==np.array(list("CAAGGA"))).sum() for row in df.loc[:, "46":"51"].values]

print (df.sort_values("match",ascending=False))

#
  Speci 45 46 47 48 49 50 51  match
3    LL  A  C  A  A  G  G  A      6
4    MM  G  C  A  A  G  G  G      5
0    PP  A  T  A  -  G  G  A      4
2    KK  A  T  -  A  G  -  A      3
1    JJ  G  T  A  -  T  A  G      1
5    NN  C  -  G  T  C  C  T      0

Answer 3

my_str <- function(df){
  nm <- names(df)
   # READ THE DATA IN
  string <- unlist(strsplit(readline("string: "),""))
  ColF <- grep(readline("ColF (Column from): "), nm)
  ColT <- grep(readline("ColT ( Column To ): "), nm)

  # COMPUTE THE MATCHES
  A <- colSums(t(df[ColF:ColT]) == string)
  B <- sort(setNames(A,df[,"Speci"]),decreasing = T)
  data.frame(Speci = names(B),Matches = B,row.names = NULL)
}

现在运行 my_str(data) 其中数据是您指定的数据帧

my_str(a)
string: CAAGGA
ColF (Column from): 46
ColT ( Column To ): 51
  Speci Matches
1    LL       6
2    MM       5
3    PP       4
4    KK       3
5    JJ       1
6    NN       0

输入PYTHON:

def my_str(df):
  string = pd.np.array(list(input("string: ")))
  ColF = input("ColF (Column from): ")
  ColT = input("ColT (Column to): ")

  A = (df.loc[:,ColF:ColT]==string[None,:]).sum(1).sort_values(ascending = False)
  return pd.DataFrame({'Speci': df['Speci'][A.index],'Matches' : A})

现在运行 my_str(data) 其中数据是您指定的数据帧

my_str(df)

string: CAAGGA

ColF (Column from): 46

ColT (Column to): 51
Out[77]: 
  Speci  Matches
3    LL        6
4    MM        5
0    PP        4
2    KK        3
1    JJ        1
5    NN        0

Answer 4

您可以在Python中使用以下解决方案：

col1 = '46'
col2 = '51'
inp = 'CAAGGA'   

result = (df.loc[:, col1:col2] == np.array(list(inp))).sum(axis=1)
result.index = df['Speci']
print(result.sort_values(ascending=False)[:3])

输出：

Speci
LL    6
MM    5
PP    4
dtype: int64

匹配 DataFrame 列中的字符串

Match string from DataFrame columns

python

r

string-matching

dataframe