Python 将多个文件中的所有列合并为一行

打开文件中的所有CSV（名称以数字结尾）

然后获取列“IMO”（在每个选定文件中）以将它们连接到“df”数据帧中：

import pandas as pd

df = pd.concat([pd.read_csv(path + '/' + f) for f in all_names if f.split('_')[3][:-4].isdigit()]['IMO'])

但是我想在一行中完成它（纯粹的挑战，没有别的）

到目前为止，它返回了一个错误：

IndexError: list index out of range

以下是

打印（所有名称）

的结果：

---

使用pandas筛选错误的文件名和参数

usecols

仅用于筛选列

IMO

<在

pandas

中，code>str[3]未失败，但如果

4.

th列表不存在，则返回

NaN

#one line solution
df = pd.concat([pd.read_csv(path + '/' + f, usecols=['IMO']) for f in pd.Series(all_names)[pd.Series(all_names).str.split('_').str[3].str[:-4].str.isdigit().fillna(False)]])

这与：

s = pd.Series(all_names)
v = s[s.str.split('_').str[3].str[:-4].str.isdigit().fillna(False)]
df = pd.concat([pd.read_csv(path + '/' + f, usecols=['IMO']) for f in v)

验证：

all_names = ['AIS_SIGHTINGS_Q1_2009.csv', 'AIS_SIGHTINGS_Q1_2009_corrected.csv', 'AIS_SIGHTINGS_Q1_2009_corrected_short.csv', 'AIS_SIGHTINGS_Q1_2010.csv', 'AIS_SIGHTINGS_Q1_2011.csv', 'AIS_SIGHTINGS_Q1_2012.csv', 'AIS_SIGHTINGS_Q1_2013.csv', 'AIS_SIGHTINGS_Q1_2014.csv', 'AIS_SIGHTINGS_Q2_2009.csv', 'AIS_SIGHTINGS_Q2_2010.csv', 'AIS_SIGHTINGS_Q2_2011.csv', 'AIS_SIGHTINGS_Q2_2012.csv', 'AIS_SIGHTINGS_Q2_2013.csv', 'AIS_SIGHTINGS_Q2_2014.csv', 'AIS_SIGHTINGS_Q3_2009.csv', 'AIS_SIGHTINGS_Q3_2010.csv', 'AIS_SIGHTINGS_Q3_2011.csv', 'AIS_SIGHTINGS_Q3_2012.csv', 'AIS_SIGHTINGS_Q3_2013.csv', 'AIS_SIGHTINGS_Q3_2014.csv', 'AIS_SIGHTINGS_Q4_2009.csv', 'AIS_SIGHTINGS_Q4_2010.csv', 'AIS_SIGHTINGS_Q4_2011.csv', 'AIS_SIGHTINGS_Q4_2012.csv', 'AIS_SIGHTINGS_Q4_2013.csv', 'AIS_SIGHTINGS_Q4_2014.csv', 'a_few_boats_AIS.csv', 'unique_boat_names.csv', 'unique_ports.csv', 'unique_vessel.csv']

s = pd.Series(all_names)
v = s[s.str.split('_').str[3].str[:-4].str.isdigit().fillna(False)]
print (v)

0     AIS_SIGHTINGS_Q1_2009.csv
3     AIS_SIGHTINGS_Q1_2010.csv
4     AIS_SIGHTINGS_Q1_2011.csv
5     AIS_SIGHTINGS_Q1_2012.csv
6     AIS_SIGHTINGS_Q1_2013.csv
7     AIS_SIGHTINGS_Q1_2014.csv
8     AIS_SIGHTINGS_Q2_2009.csv
9     AIS_SIGHTINGS_Q2_2010.csv
10    AIS_SIGHTINGS_Q2_2011.csv
11    AIS_SIGHTINGS_Q2_2012.csv
12    AIS_SIGHTINGS_Q2_2013.csv
13    AIS_SIGHTINGS_Q2_2014.csv
14    AIS_SIGHTINGS_Q3_2009.csv
15    AIS_SIGHTINGS_Q3_2010.csv
16    AIS_SIGHTINGS_Q3_2011.csv
17    AIS_SIGHTINGS_Q3_2012.csv
18    AIS_SIGHTINGS_Q3_2013.csv
19    AIS_SIGHTINGS_Q3_2014.csv
20    AIS_SIGHTINGS_Q4_2009.csv
21    AIS_SIGHTINGS_Q4_2010.csv
22    AIS_SIGHTINGS_Q4_2011.csv
23    AIS_SIGHTINGS_Q4_2012.csv
24    AIS_SIGHTINGS_Q4_2013.csv
25    AIS_SIGHTINGS_Q4_2014.csv
dtype: object

此代码的最终（工作）版本如下：

df=pd.concat（[pd.read_csv（path+'/'+f，usecols=['IMO']），如果f.split（'.）[0][-1].isdigit（）]），则所有名称中的f都应为[pd.read_csv（path+'/'+f，usecols=['IMO']）

我还没有尝试过你的版本，但它看起来应该可以正常工作（如果你解决了括号问题；）。

---

谢谢你的回答。

什么是

所有的名字

，你在检查什么情况？

all_names = ['AIS_SIGHTINGS_Q1_2009.csv', 'AIS_SIGHTINGS_Q1_2009_corrected.csv', 'AIS_SIGHTINGS_Q1_2009_corrected_short.csv', 'AIS_SIGHTINGS_Q1_2010.csv', 'AIS_SIGHTINGS_Q1_2011.csv', 'AIS_SIGHTINGS_Q1_2012.csv', 'AIS_SIGHTINGS_Q1_2013.csv', 'AIS_SIGHTINGS_Q1_2014.csv', 'AIS_SIGHTINGS_Q2_2009.csv', 'AIS_SIGHTINGS_Q2_2010.csv', 'AIS_SIGHTINGS_Q2_2011.csv', 'AIS_SIGHTINGS_Q2_2012.csv', 'AIS_SIGHTINGS_Q2_2013.csv', 'AIS_SIGHTINGS_Q2_2014.csv', 'AIS_SIGHTINGS_Q3_2009.csv', 'AIS_SIGHTINGS_Q3_2010.csv', 'AIS_SIGHTINGS_Q3_2011.csv', 'AIS_SIGHTINGS_Q3_2012.csv', 'AIS_SIGHTINGS_Q3_2013.csv', 'AIS_SIGHTINGS_Q3_2014.csv', 'AIS_SIGHTINGS_Q4_2009.csv', 'AIS_SIGHTINGS_Q4_2010.csv', 'AIS_SIGHTINGS_Q4_2011.csv', 'AIS_SIGHTINGS_Q4_2012.csv', 'AIS_SIGHTINGS_Q4_2013.csv', 'AIS_SIGHTINGS_Q4_2014.csv', 'a_few_boats_AIS.csv', 'unique_boat_names.csv', 'unique_ports.csv', 'unique_vessel.csv']

s = pd.Series(all_names)
v = s[s.str.split('_').str[3].str[:-4].str.isdigit().fillna(False)]
print (v)

0     AIS_SIGHTINGS_Q1_2009.csv
3     AIS_SIGHTINGS_Q1_2010.csv
4     AIS_SIGHTINGS_Q1_2011.csv
5     AIS_SIGHTINGS_Q1_2012.csv
6     AIS_SIGHTINGS_Q1_2013.csv
7     AIS_SIGHTINGS_Q1_2014.csv
8     AIS_SIGHTINGS_Q2_2009.csv
9     AIS_SIGHTINGS_Q2_2010.csv
10    AIS_SIGHTINGS_Q2_2011.csv
11    AIS_SIGHTINGS_Q2_2012.csv
12    AIS_SIGHTINGS_Q2_2013.csv
13    AIS_SIGHTINGS_Q2_2014.csv
14    AIS_SIGHTINGS_Q3_2009.csv
15    AIS_SIGHTINGS_Q3_2010.csv
16    AIS_SIGHTINGS_Q3_2011.csv
17    AIS_SIGHTINGS_Q3_2012.csv
18    AIS_SIGHTINGS_Q3_2013.csv
19    AIS_SIGHTINGS_Q3_2014.csv
20    AIS_SIGHTINGS_Q4_2009.csv
21    AIS_SIGHTINGS_Q4_2010.csv
22    AIS_SIGHTINGS_Q4_2011.csv
23    AIS_SIGHTINGS_Q4_2012.csv
24    AIS_SIGHTINGS_Q4_2013.csv
25    AIS_SIGHTINGS_Q4_2014.csv
dtype: object