python之函数返回数据框

1.原始文件

##gff-version 3
Chr1A   IWGSC_v2.1      gene    40098   70338   33      -       .       ID=TraesCS1A03G0000200;previous_id=TraesCS1A02G000100;primconf=HC;Name=TraesCS1A03G0000200;cds=CDS_OK;mapping=fullMatchWithMissmatches
Chr1A   IWGSC_v2.1      mRNA    40098   70338   .       -       .       ID=TraesCS1A03G0000200.1;Parent=TraesCS1A03G0000200;Note=TraesCS1A01G000100;primconf=HC;Name=TraesCS1A03G0000200.1;secconf=HC2;cds=CDS_OK;mapping=fullMatchWithMissmatches;previous_id=TraesCS1A02G000100.1
Chr1A   IWGSC_v2.1      three_prime_UTR 40098   40731   .       -       .       ID=TraesCS1A03G0000200.1.utr3p1;Parent=TraesCS1A03G0000200.1
Chr1A   IWGSC_v2.1      exon    40098   40731   .       -       .       ID=TraesCS1A03G0000200.1.exon1;Parent=TraesCS1A03G0000200.1
Chr1A   IWGSC_v2.1      three_prime_UTR 58474   58507   .       -       .       ID=TraesCS1A03G0000200.1.utr3p2;Parent=TraesCS1A03G0000200.1
Chr1A   IWGSC_v2.1      exon    58474   58897   .       -       .       ID=TraesCS1A03G0000200.1.exon2;Parent=TraesCS1A03G0000200.1
Chr1A   IWGSC_v2.1      CDS     58508   58768   .       -       0       ID=TraesCS1A03G0000200.1.CDS1;Parent=TraesCS1A03G0000200.1
Chr1A   IWGSC_v2.1      five_prime_UTR  58769   58897   .       -       .       ID=TraesCS1A03G0000200.1.utr5p1;Parent=TraesCS1A03G0000200.1
Chr1A   IWGSC_v2.1      exon    70089   70338   .       -       .       ID=TraesCS1A03G0000200.1.exon3;Parent=TraesCS1A03G0000200.1
Chr1A   IWGSC_v2.1      five_prime_UTR  70089   70338   .       -       .       ID=TraesCS1A03G0000200.1.utr5p2;Parent=TraesCS1A03G0000200.1
Chr1A   IWGSC_v2.1      gene    70239   89245   35      +       .       ID=TraesCS1A03G0000400;previous_id=TraesCS1A02G000200;primconf=HC;Name=TraesCS1A03G0000400;cds=CDS_OK;mapping=fullPerfectMatch
Chr1A   IWGSC_v2.1      mRNA    70239   89245   .       +       .       ID=TraesCS1A03G0000400.1;Parent=TraesCS1A03G0000400;Note=TraesCS1A01G000200;primconf=HC;Name=TraesCS1A03G0000400.1;secconf=HC2;cds=CDS_OK;mapping=fullPerfectMatch;previous_id=TraesCS1A02G000200.1

2.目的文件：

TraesCS1A02G002100      bad
TraesCS1A02G002200      bad
TraesCS1A02G002900      bad
TraesCS1A02G003200      bad
TraesCS1A02G003300      bad
TraesCS1A02G003700      good
TraesCS1A02G003900      bad
TraesCS1A02G004100      bad
TraesCS1A02G004300      bad
TraesCS1A02G004700      bad
TraesCS1A02G004800      bad
TraesCS1A02G004900      good
TraesCS1A02G005700      good

3.代码：

# lin_whether_1st_intron_longest.py
#! /usr/bin/env python
#统计第一个内含子是否是最长的，如果是输出good,否则输出bad
#usage: python lin_whether_1st_intron_longest.py Ta_genomeplus.gff5-1 > Ta_genomeplus.gff5-120824
#usage: python lin_whether_1st_intron_longest.py Ta_genomeminus.gff5-1 > Ta_genomeminus.gff5-120824
import pandas as pddef outputlist1(f1):list1 = []list2 = []list21 = []df1=pd.read_table(f1,index_col=0)df1["id1"]=df1.indexdf1["id1_start_end"]=df1["id1"]+","+df1["start"].astype(str)+","+df1["end"].astype(str)df2=df1.iloc[:,[3]]df3 = df2.groupby("id").apply(lambda x: x["id1_start_end"].tolist())for i in range(len(df3)):list1.append(",".join(df3[i]))# print(list1)for i in list1:i=i.strip().split(",")# " ".join(i)if len(i)>=9:for j in range(2,len(i)-1,3):list2.append(i[0])list2.append(str(int(i[j+2])-int(i[j])-1))else:continue# print(list2)# b=open("47out2.txt","w")# def output_length(list02):# b.write("id" + "\t" + "length"+"\n")for i in range(len(list2)):# list2[i]=list2[i].strip().split()# print(list2[i])if i % 2 == 0:#         # b.write(str(list2[i])+"\t"+str(list2[i+1])+"\t"+str(list2[i+2])+"\n")#         # print(str(list2[i+1])+"\t"+str(list2[i+2])+"\t"+str(list2[i]))#         b.write(str(list2[i])+"\t"+str(list2[i+1])+"\n")list21.append(list2[i:i+2])return list21def outputlist2(f2):list31 = []list32 = []list4 = []list41=[]df21 = pd.DataFrame(f2)# df21=pd.read_table(df21)df21.columns = ['id', 'length']df21=df21.set_index("id")# df21=f2df21["id1"]=df21.indexdf21["length1"]=df21["length"].astype(str)df21["id1_length"]=df21["id1"]+","+df21["length"].astype(str)df22=df21.iloc[:,[2]]df23 = df22.groupby("id").apply(lambda x: x["length1"].tolist())for i in range(len(df23)):list31.append(",".join(df23[i]))#新的数据框2df32=df21.iloc[:,[3]]df33 = df32.groupby("id").apply(lambda x: x["id1_length"].tolist())# print(df23)for i in range(len(df33)):list32.append(",".join(df33[i]))# list3=[int(i) for i in list3]# print(list32)# print(list3[1])# print(max(list3[1]))for i in range(len(list31)):list32[i] = list32[i].strip().split(",")list31[i]=list31[i].strip().split(",")list31[i]=[int(k) for k in list31[i]]# print(max(list3[i]))# for j in range(len(list3[i])):if list31[i][0]==max((list31[i])):list4.append(list32[i][0])list4.append("good")else:list4.append(list32[i][0])list4.append("bad")for i in range(len(list4)):if i % 2==0:print(str(list4[i])+"\t"+str(list4[i+1]))def outputlist3(f2):list31 = []list32 = []list4 = []list41=[]df21 = pd.DataFrame(f2)# df21=pd.read_table(df21)df21.columns = ['id', 'length']df21=df21.set_index("id")# df21=f2df21["id1"]=df21.indexdf21["length1"]=df21["length"].astype(str)df21["id1_length"]=df21["id1"]+","+df21["length"].astype(str)df22=df21.iloc[:,[2]]df23 = df22.groupby("id").apply(lambda x: x["length1"].tolist())for i in range(len(df23)):list31.append(",".join(df23[i]))#新的数据框2df32=df21.iloc[:,[3]]df33 = df32.groupby("id").apply(lambda x: x["id1_length"].tolist())# print(df23)for i in range(len(df33)):list32.append(",".join(df33[i]))# list3=[int(i) for i in list3]# print(list32)# print(list3[1])# print(max(list3[1]))for i in range(len(list31)):list32[i] = list32[i].strip().split(",")list31[i]=list31[i].strip().split(",")list31[i]=[int(k) for k in list31[i]]# print(max(list3[i]))# for j in range(len(list3[i])):if list31[i][0]==max((list31[i])):list4.append(list32[i][0])list4.append("good")else:list4.append(list32[i][0])list4.append("bad")for i in range(len(list4)):if i % 2==0:print(str(list4[i])+"\t"+str(list4[i+1]))
import argparse
import os
parser = argparse.ArgumentParser(description="Advanced screening always by hash")
parser.add_argument("-f1","--file1",help="the original file,tabulated,make sure do not contain blank line")
args = parser.parse_args()
with open (args.file1,"r") as f1:if "plus" in args.file1:df01=outputlist1(args.file1)outputlist2(df01)else:df01=outputlist1(args.file1)outputlist3(df01)