Big data's Analysis of practical Learning Notes based on python-DataFrame of pandas

Then in the previous article, we went on to DataFrame in pandas. Without saying much, we went straight to the code with comments.

# the operation of dataframe is nothing more than adding, deleting, changing and checking

From pandas import Series

From pandas import DataFrame

Df=DataFrame ({'age':Series ([18d20 ~ 30]))

'name':Series ([' x1pm / x2pm / / x3'])

})

Print (df)

''

Access column: variable name [column name]

Access line: variable name [nRom] access line n to line mmur1

Access blocks (rows and columns): variable names .iloc [n1:n2, m1:m2] access data from N1 to N2-1 rows and M1 to m2-1 columns

Access the specified location: variable name .at [row index, column name]

''

# access column

A=df ['age']

Print (a)

# access lines

B=df [1:3]

Print (b)

# access block

C=df.iloc [0:4,0:2]

Print (c)

# access the specified location

D=df.at [0reachingname']

Print (d)

# add columns

Df ['address'] = [' Earth', 'moon', 'Mars']

Print (df)

# Delete columns

# del df ['address']

# add lines

Df.loclen (df)] = [40, 'x4mom,' Jupiter']

Print (df)

# Delete rows, according to row index

# df.drop (1)

Isn't it easy? As long as you have the foundation of python, you can do it in minutes.