Python;将数据帧输出写入不同的子目录

Question

我正在从当前工作目录运行脚本。通过我的脚本，我循环遍历当前工作目录的子目录。每个子目录都包含脚本中提到的 3 个文件，对于每个子目录，我将这 3 个文件合并到一个数据帧。正如我现在的脚本所示，它仅将一个子目录的合并数据帧写入当前工作目录。我想要的是 csv 文件，其中每个子目录的合并数据帧保存在该子目录中，或者每个子目录的数据帧连接到一个大输出文件的文件。在我的脚本中，输出文件中只有一个子目录的输出。

我的脚本如下:

print('Start merging contig files')

for root, dirs, files in os.walk(os.getcwd()):
    filepath = os.path.join(root, 'genes.faa.genespercontig.csv')
    if os.path.isfile(filepath):
        with open(filepath, 'r') as f1:
            df1 = pd.read_csv(f1, header=None, delim_whitespace=True, names = ["contig", "genes"])
            df1['genome'] = os.path.basename(os.path.dirname(filepath))

    filepath = os.path.join(root, 'hmmer.analyze.txt.results.txt')
    if os.path.isfile(filepath):
        with open(filepath, 'r') as f2:
            df2 = pd.read_csv(f2, header=None, delim_whitespace=True, names = ["contig", "SCM"])
            df2['genome'] = os.path.basename(os.path.dirname(filepath))

    filepath = os.path.join(root, 'genes.fna.output_blastplasmiddb.out.count_plasmiddbhit.out')
    if os.path.isfile(filepath):
        with open(filepath, 'r') as f3:
            df3 = pd.read_csv(f3, header=None, delim_whitespace=True, names = ["contig", "plasmid_genes"])
            df3['genome'] = os.path.basename(os.path.dirname(filepath))

#merge dataframes
dfmerge1 = pd.merge(df1, df2, on=['genome', 'contig'], how='outer')
df_end = pd.merge(dfmerge1, df3, on=['genome', 'contig'], how='outer')      

df_end.to_csv('outputgenesdf.csv')

Answer 1

试试这个:

df_end.to_csv(os.path.join(root, 'outputgenesdf.csv'))

PS 确保该命令位于 for 循环

print('Start merging contig files')

for root, dirs, files in os.walk(os.getcwd()):
    filepath = os.path.join(root, 'genes.faa.genespercontig.csv')
    if os.path.isfile(filepath):
        with open(filepath, 'r') as f1:
            df1 = pd.read_csv(f1, header=None, delim_whitespace=True, names = ["contig", "genes"])
            df1['genome'] = os.path.basename(os.path.dirname(filepath))

    filepath = os.path.join(root, 'hmmer.analyze.txt.results.txt')
    if os.path.isfile(filepath):
        with open(filepath, 'r') as f2:
            df2 = pd.read_csv(f2, header=None, delim_whitespace=True, names = ["contig", "SCM"])
            df2['genome'] = os.path.basename(os.path.dirname(filepath))

    filepath = os.path.join(root, 'genes.fna.output_blastplasmiddb.out.count_plasmiddbhit.out')
    if os.path.isfile(filepath):
        with open(filepath, 'r') as f3:
            df3 = pd.read_csv(f3, header=None, delim_whitespace=True, names = ["contig", "plasmid_genes"])
            df3['genome'] = os.path.basename(os.path.dirname(filepath))

    #merge dataframes
    dfmerge1 = pd.merge(df1, df2, on=['genome', 'contig'], how='outer')
    df_end = pd.merge(dfmerge1, df3, on=['genome', 'contig'], how='outer')      

    df_end.to_csv(os.path.join(root, 'outputgenesdf.csv'))