pandas module 1 - cookbook

1. Idioms(习语)

（1）if-then on one column



（2）if-then with assignment to 2 columns



（3）to do the -else



（4）use the mask



（5）if-then-else using numpy's where()



（6）Split a frame with a boolean criterion



（7） Select with multi-column criteria



（8）select rows with data closest to certain value using argsort



（9）Dynamically reduce a list of criteria using a binary operators

2. Selection

1. DataFrame

（1） Using both row labels and value conditionals



（2）Use loc or iloc slicing



（3）using (~) to make a mask



2. Pannels(面板) -- adding a new dimension 



3. creating a new columns (applymap)



4. keep other columns when using min() with groupby

3. Multi-Indexing

1. creating a multi-index from a labeled frame





2. Performing arthmetic with a multi-index that needs broadcasting



3. slicing a multi-index with xs method1



4. sort with a multi-index

4. Missing Data

Fill forward a reversed timeseries

5. Grouping

1. Basic grouping with apply



2. using get_group



3. In a group apply to different items



4. Expanding apply



5. Replacing some values



6. sort groups by aggregated(聚合) data



7. create multiple aggregated columns



8. create a value counts column and reassign back to the DataFrame



9. shift groups in a column



10. select row with max value from each group



11. grouping like python's itertools.groupby



12. create a list of dataframes, split using a delineation based on logic included in rows



13. partial sums(部分和) and subtotals(小计)



14. frequency table like plyr in R



15. using apply to turning embeded lists into a multi-index frame



16. Rolling apply with a DataFrame returning a Series



17. rolling apply with a DataFrame returning a Scalar(Volume Weighted Average Price)

6. Timeseries

1. calculate the first day of the month for each entry in a DatetimeIndex

7. Merge

1. append two dataframes with overlapping index



2. self join of a dataframe

8. Plotting

9. Data In/Out

1. CSV

(1) sample



(2) skip row between beader and data





2. 二进制文件

10. Timedeltas

1. using time deltas





2. datetime can be set to NaT



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