如何使用 pandas 拆分数据框

Question

我的列值类似于 1ST:[70]2ND:[71]3RD:[71]S1:[71]4TH:[77]5TH:[78]6TH:[78]S2:[78] FIN:[75] 在 csv 中，需要将所有合并的内容提取到单独的列中，如何做 pandas

需要O/p赞：

 1ST 2ND 3RD  S1 4TH 5TH 6TH  S2 FIN
0  70  71  71  71  77  78  78  78  75

我在这里粘贴了该列值的一些行。

1ST:[80]2ND:[79]3RD:[75]S1:[78]4TH:[76]5TH:[80]6TH:[87]S2:[81]FIN:[80]
1ST:[75]2ND:[74]3RD:[81]S1:[77]4TH:[80]5TH:[78]6TH:[87]S2:[82]FIN:[80]
1ST:[58]2ND:[54]3RD:[65]S1:[59]4TH:[80]5TH:[72]6TH:[74]S2:[75]FIN:[67]
1ST:[90]2ND:[91]3RD:[82]S1:[88]4TH:[84]5TH:[88]6TH:[87]S2:[86]FIN:[87]
1ST:[83]2ND:[79]3RD:[82]S1:[81]4TH:[85]5TH:[84]6TH:[90]S2:[86]FIN:[84]

在数据框中，我有一列包含以上值。我需要分成不同的列，值将在行中。

Answer 1

您的问题似乎令人困惑。您的 objective 从解决方案结构方面看是什么？

你的文件有这样的价值 1ST:[70]2ND:[71]3RD:[71]S1:[71]4TH:[77]5TH:[78]6TH:[78]S2:[78]FIN:[75]

你想要的输出应该是这样的

  1ST 2ND 3RD  S1 4TH 5TH 6TH  S2 FIN
0  70  71  71  71  77  78  78  78  75

或者像这样

现在，从给定输入获取输出的方法

import pandas as pd
# consider your input is string (you can use csv)
file_val = "1ST:[70]2ND:[71]3RD:[71]S1:[71]4TH:[77]5TH:[78]6TH:[78]S2:[78]FIN:[75]"

df = pd.DataFrame([i.split(':') for i in file_val.replace('[',"").split(']') if i!=""])
print(df)
     0   1
0  1ST  70
1  2ND  71
2  3RD  71
3   S1  71
4  4TH  77
5  5TH  78
6  6TH  78
7   S2  78
8  FIN  75

请分享 csv 文件或几行的快照，以便我能够根据您的要求生成输出。

根据您的格式返回最终解决方案

# reading data 
with open('sample.csv') as f:
    dat = file.read(f)

# spliting rows 
dat1 = dat.split(\n)

# method to convert each row to dict
def row_to_dict(row):
    return dict([i.split(":") for i in row.replace('[',"").split(']') if i!=""])

# now apply method to each row of dat1 and create single dataframe out of it 
# that is nothing but final output

res = pd.DataFrame(map(lambda x:row_to_dict(x), dat1))

print(res)
  1ST 2ND 3RD 4TH 5TH 6TH FIN  S1  S2
0  80  79  75  76  80  87  80  78  81
1  75  74  81  80  78  87  80  77  82
2  58  54  65  80  72  74  67  59  75
3  90  91  82  84  88  87  87  88  86
4  83  79  82  85  84  90  84  81  86

Answer 2

在R中找到上面的结果

a1=read.csv("c:/Users/Dell/Desktop/NewText.txt",header = FALSE)
a1$V1=as.character(a1$V1)
g1=NULL
g2=NULL
l=list()
for(i in 1:nrow(a1))
    {
        g1=strsplit(a1$V1[i],"]")

        g1=strsplit(g1[[1]],":\[")

          g2=data.frame(g1)
          g2[] <- lapply(g2, as.character)
          colnames(g2)=g2[1,]
          g2=g2[-1,]
          l[[i]]=g2         
}
l=do.call('rbind',l)

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