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Chapter 2 - Data Preparation Basics

Segment 4 - Concatenating and transforming data

import numpy as np
import pandas as pd

from pandas import Series, DataFrame

DF_obj = pd.DataFrame(np.arange(36).reshape(6,6))
DF_obj

DF_obj_2 = pd.DataFrame(np.arange(15).reshape(5,3))
DF_obj_2

Concatenating data

pd.concat([DF_obj,DF_obj_2],axis=1)

pd.concat([DF_obj,DF_obj_2])

Transforming data

Dropping data

DF_obj.drop([0,2])

DF_obj.drop([0,2],axis=1)

Adding data

series_obj = Series(np.arange(6))
series_obj.name = "added_variable"
series_obj

0    0
1    1
2    2
3    3
4    4
5    5
Name: added_variable, dtype: int64

variable_added = DataFrame.join(DF_obj,series_obj)
variable_added

added_datatable = variable_added.append(variable_added, ignore_index=False)
added_datatable

added_datatable = variable_added.append(variable_added, ignore_index=True)
added_datatable

Sorting data

DF_sorted = DF_obj.sort_values(by=(5),ascending=[False])
DF_sorted

Python for Data Science - Concatenating and transforming data

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原文地址：https://www.cnblogs.com/keepmoving1113/p/14223109.html