Added homework on pandas#5
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krglkvrmn
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Dec 10, 2022
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Всё круто, жалко, что без второй части
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| rrna_gff_df = read_gff('data/rrna_annotation.gff') | ||
| alignment_bed_df = read_bed('data/alignment.bed') |
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Если код подразумевает работу с данными из каких-то файлов, то эти файлы обязательно нужно класть в репозиторий и указывать относительный путь до них. Исключение только одно - слишком большие файлы, в таком случае можно заливать их маленький кусочек.
| # Function for reading gff files | ||
| def read_gff(path_to_gff): | ||
| gff_header = ['chromosome', 'source', 'type', 'start', 'end', 'score', 'strand', 'phase', 'attributes'] | ||
| return pd.read_csv(path_to_gff, sep='\t', names=gff_header, comment = '#') |
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| return pd.read_csv(path_to_gff, sep='\t', names=gff_header, comment = '#') | |
| return pd.read_csv(path_to_gff, sep='\t', names=gff_header, comment='#') |
| rrnas_by_types = pd.DataFrame({'count' : rrna_gff_df.groupby(['chromosome','attributes']).size()}).reset_index() | ||
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| # Merging gff and bed files | ||
| merged_df = pd.merge(rrna_gff_df, alignment_bed_df, how='outer', left_on=['chromosome'], right_on=['chromosome']) |
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Можно чуть проще
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| merged_df = pd.merge(rrna_gff_df, alignment_bed_df, how='outer', left_on=['chromosome'], right_on=['chromosome']) | |
| merged_df = pd.merge(rrna_gff_df, alignment_bed_df, how='outer', on='chromosome') |
| plt.xticks(rotation=90, size=10); | ||
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| # Extracting rRNAs which intersect with alignment | ||
| rrnas_align_intersect = merged_df[(merged_df['start_x'] >= merged_df['start_y']) & (merged_df['end_x'] <= merged_df['end_y'])] |
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Рабочий вариант. Можно ещё через query, ИМХО так чуть лаконичнее
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| rrnas_align_intersect = merged_df[(merged_df['start_x'] >= merged_df['start_y']) & (merged_df['end_x'] <= merged_df['end_y'])] | |
| rrnas_align_intersect = merged_df.query('start_x >= start_y and end_x <= end_y') |
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