fixed stuff, conf.py, index.rst

dox/conf.py

@@ -50,6 +50,7 @@ extensions = [
 
     # markdown sources support
     'recommonmark',
+    'sphinx_markdown_tables',
 ]
 numpydoc_show_class_members = False
 automodsumm_inherited_members = True

dox/indexing_help.md

@@ -22,14 +22,16 @@ each column separately.
 
 So maybe a first example gives an rough idea:
 ```
->> d
+>>> s = pd.Series([11] * 4 )
+>>> d = DictOfSeries(dict(a=s[:2]*6, b=s[2:4]*7, c=s[:2]*8, d=s[1:3]*9))
+>>> d
     a |     b |     c |     d | 
 ===== | ===== | ===== | ===== | 
 0  66 | 2  77 | 0  88 | 1  99 | 
 1  66 | 3  77 | 1  88 | 2  99 | 
 
 
->> d.aloc[[1,2], ['a', 'b', 'd', 'x']]
+>>> d.aloc[[1,2], ['a', 'b', 'd', 'x']]
     a |     b |     d | 
 ===== | ===== | ===== | 
 1  66 | 2  77 | 1  99 | 
@@ -94,37 +96,44 @@ Indexer Table
 | example | type | on  | like `.loc` | handling | conditions / hints | link |
 | ------- | ---- | --- | ----------- | -------- | ------------------ | ---- |
 | `.aloc[any, 'a']`         | scalar               | columns |no | select graceful | - | [cols](#select-columns-gracefully)|
-
-
-fooo
-----
-|[Column indexer](#select-columns-gracefully)| ---- | --- | ----------- | -------- | ------------------ | ---- |
+|[Column indexer](#select-columns-gracefully)| 
 | `.aloc[any, 'a']`         | scalar               | columns |no | select graceful | - | [cols](#select-columns-gracefully)|
 | `.aloc[any, 'b':'z']`       | slice                | columns |yes| slice | - | [cols](#select-columns-gracefully)|
 | `.aloc[any, ['a','c']]`     | list-like            | columns |no | filter graceful | - | [cols](#select-columns-gracefully)|
 | `.aloc[any [True,False]]`   | bool list-like       | columns |yes| take `True`'s | length must match nr of columns | [cols](#select-columns-gracefully)|
-| `.aloc[any, s]`             | pandas.Series        | columns |no | like list,  | only `s.values` are evaluated | [cols](#select-columns-gracefully)|
-| `.aloc[any, bs]`            | bool pandas.Series   | columns |yes| like bool-list | see there | [cols](#select-columns-gracefully)|
-|[Row indexer](#selecting-rows-a-smart-way)|    ---- | --- | ----------- | -------- | ------------------ | ---- |                                           
+| `.aloc[any, s]`             | Series        | columns |no | like list,  | only `s.values` are evaluated | [cols](#select-columns-gracefully)|
+| `.aloc[any, bs]`            | bool Series   | columns |yes| like bool-list | see there | [cols](#select-columns-gracefully)|
+|[Row indexer](#selecting-rows-a-smart-way)|  
 | `.aloc[7, any]`             | scalar               | rows    |no | translate to `.loc[key:key]` | - | [rows](#selecting-rows-a-smart-way) |
 | `.aloc[3:42, any]`          | slice                | rows    |yes| slice | - | | 
 | `.aloc[[1,2,24], any]`      | list-like            | rows    |no | filter graceful | - | [rows](#selecting-rows-a-smart-way) |
 | `.aloc[[True,False], any]`  | bool list-like       | rows    |yes| take `True`'s | length must match nr of (all selected) columns | [blist](#boolean-array-likes-as-row-indexer)|
-| `.aloc[s, any]`             | pandas.Series        | rows    |no | like `.loc[s.index]` | - | [ser](#pandasseries-and-boolean-pandasseries-as-row-indexer) |
-| `.aloc[bs, any]`            | bool pandas.Series   | rows    |no | align + just take `True`'s  | evaluate `usebool`-keyword |  [ser](#pandasseries-and-boolean-pandasseries-as-row-indexer)|
+| `.aloc[s, any]`             | Series        | rows    |no | like `.loc[s.index]` | - | [ser](#pandasseries-and-boolean-pandasseries-as-row-indexer) |
+| `.aloc[bs, any]`            | bool Series   | rows    |no | align + just take `True`'s  | evaluate `usebool`-keyword |  [ser](#pandasseries-and-boolean-pandasseries-as-row-indexer)|
 | `.aloc[[[s],[1,2,3]], any]` | nested list-like     | both    | ? | one row-indexer per column | outer length must match nr of (selected) columns | [nlist](#nested-lists-as-row-indexer) |
-|[2D-indexer](#the-power-of-2d-indexer)| ---- | --- | ----------- | -------- | ------------------ | ---- |                                                
+|[2D-indexer](#the-power-of-2d-indexer)| 
 | `.aloc[di]`                 | dios-like            | both    |no | full align  | - | |
 | `.aloc[di, ...]`            | dios-like            | both    |no | full align | ellipsis has no effect | |
 | `.aloc[di>5]`               | bool dios-like       | both    |no | full align + take `True`'s | evaluate `usebool`-keyword | |
 | `.aloc[di>5, ...]`          | (bool) dios-like     | both    |no | full align, **no** bool evaluation | - | |
 
 Example dios
-============
+------------
 
 The dios used in the examples, unless stated otherwise:
 
 ``` 
+# generate dict
+>>> sa = pd.Series(range(0, 70, 7))
+>>> sb = pd.Series(range(5, 15, 1))
+>>> sc = pd.Series(range(7, 107, 10))
+>>> sd = pd.Series(range(0, 10, 1))
+>>> for i, s in enumerate([sa,sb,sc,sd]): s.index += i*2
+>>> d = DictOfSeries(dict(a=sa, b=sb, c=sc, d=sd))[:5]
+```
+
+Looks like so:
+```
 >>> d
     a |    b |     c |     d | 
 ===== | ==== | ===== | ===== | 
@@ -136,13 +145,13 @@ The dios used in the examples, unless stated otherwise:
 ```
 
 Select columns, gracefully
-===========================
+---------------------------
 
 **Single columns**
 
 Use `.aloc[:, key]` to select a single column gracefully. 
-The underling pandas Series is returned, if the key exist. 
-Otherwise a empty pd.Series with `dtype=object` is returned.
+The underling pandas.Series is returned, if the key exist. 
+Otherwise a empty pandas.Series with `dtype=object` is returned.
 
 ```
 >>> d.aloc[:, 'a']
@@ -207,7 +216,7 @@ eg `.loc[:, 'a':'f']`.
 
 
 Selecting Rows a smart way
-==========================
+--------------------------
 
 For scalar and array-like indexer with label values, the keys are handled gracefully, just like with 
 array-like column indexers.
@@ -255,8 +264,7 @@ If the length does not match a `IndexError` is raised:
 >>> d.aloc[[True,False,False]]
 Traceback (most recent call last):
   ...
-  f"Boolean index has wrong length: "
-IndexError: failed for column a: Boolean index has wrong length: 3 instead of 5
+  IndexError: failed for column a: Boolean index has wrong length: 3 instead of 5
 ```
 
 This can be tricky, especially if columns have different length:
@@ -271,8 +279,7 @@ This can be tricky, especially if columns have different length:
 >>> difflen.aloc[[False,True,False]]
 Traceback (most recent call last):
   ...
-  f"Boolean index has wrong length: "
-IndexError: Boolean index has wrong length: 3 instead of 2
+  IndexError: Boolean index has wrong length: 3 instead of 2
 ```
 
 pandas.Series and boolean pandas.Series as row indexer
@@ -401,7 +408,7 @@ In contrast to the 2D-indexer, we also can provide a column key, to pre-filter t
 
 
 The power of 2D-indexer
-=======================
+-----------------------
 
 Overview: