pandas

to number

df.apply(pd.to_numeric, errors='coerce')

df.fillna(0.0)

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

# 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)

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

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

xls = pd.ExcelFile('docs/20170525.xlsx')
df1 = xls.parse('Sheet 1')
df2 = xls.parse('Sheet 2')

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