# pandas
- Python Data Analysis Library
- http://pandas.pydata.org/

- http://pandas.pydata.org/pandas-docs/stable/10min.html

## to number
- dash to number
```py
df.apply(pd.to_numeric, errors='coerce')
```
- fill N/A
```py
df.fillna(0.0)
```

## column edit
- column names

```py
df.columns = ['prdcode', 'category', 'prdname', 'brand']
```

- drop

```py
# drop row 0-2
df.drop(df.index[:3], inplace=True) # row

# drop column
df.drop('column_name', 1)
df.drop('column_name', axis=1, inplace=True)
```

- reorder

```py
df2 = df[['prdcode', 'category', 'prdname', 'brand']]
df2.head()
```

## column type change

```py
df[['ZIP_NO']] = df[['ZIP_NO']].astype(str)
```

## read sheet
```py
xls = pd.ExcelFile('docs/20170525.xlsx')
df1 = xls.parse('Sheet 1')
df2 = xls.parse('Sheet 2')
```

## Tutorial
- http://pandas.pydata.org/pandas-docs/stable/tutorials.html
- 01 - Lesson: - Importing libraries - Creating data sets - Creating data frames - Reading from CSV - Exporting to CSV - Finding maximums - Plotting data
- 02 - Lesson: - Reading from TXT - Exporting to TXT - Selecting top/bottom records - Descriptive statistics - Grouping/sorting data
- 03 - Lesson: - Creating functions - Reading from EXCEL - Exporting to EXCEL - Outliers - Lambda functions - Slice and dice data
- 04 - Lesson: - Adding/deleting columns - Index operations
- 05 - Lesson: - Stack/Unstack/Transpose functions
- 06 - Lesson: - GroupBy function
- 07 - Lesson: - Ways to calculate outliers
- 08 - Lesson: - Read from Microsoft SQL databases
- 09 - Lesson: - Export to CSV/EXCEL/TXT
- 10 - Lesson: - Converting between different kinds of formats
- 11 - Lesson: - Combining data from various sources