The strongest pandas learning artifact is coming

source ：https://pandastutor.com/index.html

Pandas It is a common tool of data mining , It is very important to master the functions in the process of use . This paper will use the process of Visualization , Explain Pandas Various operations of .

sort_values

(dogs[dogs['size'] == 'medium']
 .sort_values('type')
 .groupby('type').median()
)

Execution steps ：

• size List and filter out departments and branches

• Then convert the type of the row

• according to type Columns to group , Calculate the median

selecting a column

dogs['longevity']

groupby + mean

dogs.groupby('size').mean()

Execution steps ：

• Set the data according to size Grouping

• Aggregate within a group

grouping multiple columns

dogs.groupby(['type', 'size'])

groupby + multi aggregation

(dogs
  .sort_values('size')
  .groupby('size')['height']
  .agg(['sum', 'mean', 'std'])
)

Execution steps

• according to size Columns sort the data

• according to size Grouping

• For within group height Calculate

filtering for columns

df.loc[:, df.loc['two'] <= 20]

filtering for rows

dogs.loc[(dogs['size'] == 'medium') & (dogs['longevity'] > 12), 'breed']

dropping columns

dogs.drop(columns=['type'])

joining

ppl.join(dogs)

merging

ppl.merge(dogs, left_on='likes', right_on='breed', how='left')

pivot table

dogs.pivot_table(index='size', columns='kids', values='price')

melting

dogs.melt()

pivoting

dogs.pivot(index='size', columns='kids')

stacking column index

dogs.stack()

unstacking row index

dogs.unstack()

resetting index

dogs.reset_index()

setting index

dogs.set_index('breed')

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