[英]Counting occurrence of a word in a column of a tsv file using python
Question from a python beginner! 来自python初学者的问题! I have a tsv file looking like this:
我有一个tsv文件,如下所示:
WHI5 YOR083W CDC28 YBR160W physical interactions 19823668
WHI5 YOR083W CDC28 YBR160W physical interactions 21658602
WHI5 YOR083W CDC28 YBR160W physical interactions 24186061
WHI5 YOR083W RPD3 YNL330C physical interactions 19823668
WHI5 YOR083W SWI4 YER111C physical interactions 15210110
WHI5 YOR083W SWI4 YER111C physical interactions 15210111
I would like to count all the lines containing the same word in row[3], and only output the first one with the number of occurrence in a new column. 我想计算行[3]中包含相同单词的所有行,并且只输出第一个包含新列中出现次数的行。
WHI5 YOR083W CDC28 YBR160W physical interactions 19823668 3
WHI5 YOR083W RPD3 YNL330C physical interactions 19823668 1
WHI5 YOR083W SWI4 YER111C physical interactions 15210110 2
So far I tried a combination of 'csv' and 'Counter' or 'pandas' and 'Counter' without success... 到目前为止,我尝试了'csv'和'Counter'或'pandas'和'Counter'的组合没有成功......
using pandas: 使用熊猫:
>>> import pandas as pd
>>> from io import BytesIO
>>> df = pd.read_table(BytesIO("""\
... col1 col2 col3 col4 col5 col6
... WHI5 YOR083W CDC28 YBR160W "physical interactions" 19823668
... WHI5 YOR083W CDC28 YBR160W "physical interactions" 21658602
... WHI5 YOR083W CDC28 YBR160W "physical interactions" 24186061
... WHI5 YOR083W RPD3 YNL330C "physical interactions" 19823668
... WHI5 YOR083W SWI4 YER111C "physical interactions" 15210110
... WHI5 YOR083W SWI4 YER111C "physical interactions" 15210111"""),
... delim_whitespace=True)
the pandas data-frame will look like: pandas数据框看起来像:
>>> df
col1 col2 col3 col4 col5 col6
0 WHI5 YOR083W CDC28 YBR160W physical interactions 19823668
1 WHI5 YOR083W CDC28 YBR160W physical interactions 21658602
2 WHI5 YOR083W CDC28 YBR160W physical interactions 24186061
3 WHI5 YOR083W RPD3 YNL330C physical interactions 19823668
4 WHI5 YOR083W SWI4 YER111C physical interactions 15210110
5 WHI5 YOR083W SWI4 YER111C physical interactions 15210111
[6 rows x 6 columns]
to get the count, group by col3
and take the length of each group: 得到计数,按
col3
分组并取每组的长度:
>>> df['cnt'] = df.groupby('col3')['col3'].transform(len)
>>> df
col1 col2 col3 col4 col5 col6 cnt
0 WHI5 YOR083W CDC28 YBR160W physical interactions 19823668 3
1 WHI5 YOR083W CDC28 YBR160W physical interactions 21658602 3
2 WHI5 YOR083W CDC28 YBR160W physical interactions 24186061 3
3 WHI5 YOR083W RPD3 YNL330C physical interactions 19823668 1
4 WHI5 YOR083W SWI4 YER111C physical interactions 15210110 2
5 WHI5 YOR083W SWI4 YER111C physical interactions 15210111 2
[6 rows x 7 columns]
to pick the first of each group: 选择每组的第一个:
>>> df.groupby('col3').apply(lambda obj: obj.head(n=1))
col1 col2 col3 col4 col5 col6 cnt
col3
CDC28 0 WHI5 YOR083W CDC28 YBR160W physical interactions 19823668 3
RPD3 3 WHI5 YOR083W RPD3 YNL330C physical interactions 19823668 1
SWI4 4 WHI5 YOR083W SWI4 YER111C physical interactions 15210110 2
[3 rows x 7 columns]
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