从 pandas 列中选择特定值并将它们相加

Question

我在带有格式列的 csv 文件中也有 8 个人口： pop

我正在尝试使用此代码仅提取 AD 和 DP 值：

import io
import os
import pandas as pd


def read_vcf(path1):
    with open(path1, 'r') as f:
            lines = [l for l in f if not l.startswith('##')]
    return pd.read_csv(
        io.StringIO(''.join(lines)),
        dtype={'#CHROM': str, 'POS': int, 'ID': str, 'REF': str, 'ALT': str,
               'QUAL': str, 'FILTER': str, 'INFO': str},
        sep='\t'
    ).rename(columns={'#CHROM': 'CHROM'})


def extract_AD(info):
    AD= int((info.split(':')[1]).split(',')[0])
    return AD

path1 = "C://Users//USER//Desktop//Anas/VCFs_1/test_1.vcf"

file =read_vcf(path1)


pop1 = file[["FORMAT","NEN_001","NEN_003","NEN_200","NEN_300","LAB_004","LAB_300","LAB_400","LAB_500"]]

cols_to_apply = ["NEN_001","NEN_003","NEN_200","NEN_300","LAB_004","LAB_300","LAB_400","LAB_500"]

tst1pop1 = pd.DataFrame(pop1)
AD= tst1pop1[cols_to_apply].applymap(extract_AD)
#AD= pop1["NEN_001"].apply(extract_AD)


def extract_DP(info):
    DP = info.split(':')[2:3]
    return DP

print("AD Values:"+"\n",AD)


DP= tst1pop1[cols_to_apply].applymap(extract_DP)
print("DP Values:\n",DP)


Sum1 = AD.sum(axis=1)
print(Sum1)
SumAD = sum(Sum1)
print(SumAD)

但它给了我列表中的 DP 值，所以我无法对它们求和

输出： Output

如何从列表中获取整数的 dp 值，以便按行求和？

Answer 1

这应该做吗？ ：How to remove square bracket from pandas dataframe

df['value'] = df['value'].str[0]

Answer 2

如果您想编辑 DP 的所有列，一个简单的解决方法是遍历列并更改如下值：

DP= tst1pop1[cols_to_apply].applymap(extract_DP)

for column in DP: 
    DP[column] = DP[column].str[0].astype(int)

print("DP Values:\n",DP)