Pandas 从单个文件读取多个数据集

我的文本文件包含每个数据库的表。熊猫有没有办法读取此文件并为每个数据库创建单独的数据帧

Database: ABC
+-----------------------------------------------+----------+------------+
|                    Tables                     | Columns  | Total Rows |
+-----------------------------------------------+----------+------------+
| ApplicationUpdateBankLog                      |       13 |          0 |
| ChangeLogTemp                                 |       12 |    1678363 |
| Sheet2$                                       |       10 |        359 |
| tempAllowApplications                         |        1 |          9 |
+-----------------------------------------------+----------+------------+
4 rows in set.


Database: XYZ
+--------------------------------------------------+----------+------------+
|                      Tables                      | Columns  | Total Rows |
+--------------------------------------------------+----------+------------+
| BKP_QualificationDetails_12082014                |       14 |    7959877 |
| BillNotGeneratedCount                            |       11 |       2312 |
| VVshipBenefit                                    |       19 |     197356 |
| VVBenefit_Bkup29012016                           |       19 |     101318 |
+--------------------------------------------------+----------+------------+
4 rows in set.

---

您可以使用

dict comprehension

创建

数据帧的
dict
：

import pandas as pd
from pandas.compat import StringIO

temp=u"""Database: ABC
+-----------------------------------------------+----------+------------+
|                    Tables                     | Columns  | Total Rows |
+-----------------------------------------------+----------+------------+
| ApplicationUpdateBankLog                      |       13 |          0 |
| ChangeLogTemp                                 |       12 |    1678363 |
| Sheet2$                                       |       10 |        359 |
| tempAllowApplications                         |        1 |          9 |
+-----------------------------------------------+----------+------------+
4 rows in set.


Database: XYZ
+--------------------------------------------------+----------+------------+
|                      Tables                      | Columns  | Total Rows |
+--------------------------------------------------+----------+------------+
| BKP_QualificationDetails_12082014                |       14 |    7959877 |
| BillNotGeneratedCount                            |       11 |       2312 |
| VVshipBenefit                                    |       19 |     197356 |
| VVBenefit_Bkup29012016                           |       19 |     101318 |
+--------------------------------------------------+----------+------------+
4 rows in set."""
#after testing replace 'StringIO(temp)' to 'filename.csv'
df = pd.read_csv(StringIO(temp), sep="|", names=['a', 'Tables', 'Columns', 'Total Rows'])

您可以使用
dict comprehension
创建
数据帧的
dict
：

import pandas as pd
from pandas.compat import StringIO

temp=u"""Database: ABC
+-----------------------------------------------+----------+------------+
|                    Tables                     | Columns  | Total Rows |
+-----------------------------------------------+----------+------------+
| ApplicationUpdateBankLog                      |       13 |          0 |
| ChangeLogTemp                                 |       12 |    1678363 |
| Sheet2$                                       |       10 |        359 |
| tempAllowApplications                         |        1 |          9 |
+-----------------------------------------------+----------+------------+
4 rows in set.


Database: XYZ
+--------------------------------------------------+----------+------------+
|                      Tables                      | Columns  | Total Rows |
+--------------------------------------------------+----------+------------+
| BKP_QualificationDetails_12082014                |       14 |    7959877 |
| BillNotGeneratedCount                            |       11 |       2312 |
| VVshipBenefit                                    |       19 |     197356 |
| VVBenefit_Bkup29012016                           |       19 |     101318 |
+--------------------------------------------------+----------+------------+
4 rows in set."""
#after testing replace 'StringIO(temp)' to 'filename.csv'
df = pd.read_csv(StringIO(temp), sep="|", names=['a', 'Tables', 'Columns', 'Total Rows'])

print (dfs['Database: ABC'])
                     Tables Columns Total Rows
0  ApplicationUpdateBankLog      13          0
1             ChangeLogTemp      12    1678363
2                   Sheet2$      10        359
3     tempAllowApplications       1          9

print (dfs['Database: XYZ'])
                              Tables Columns Total Rows
0  BKP_QualificationDetails_12082014      14    7959877
1              BillNotGeneratedCount      11       2312
2                      VVshipBenefit      19     197356
3             VVBenefit_Bkup29012016      19     101318