python | pandas data frame.IX[]
哎哎哎:# t0]https://www.geeksforgeeks.org/python 熊猫 dataframe-ix/
Python 是进行数据分析的优秀语言，主要是因为以数据为中心的 Python 包的奇妙生态系统。 【熊猫】 就是其中一个包，让导入和分析数据变得容易多了。
熊猫**DataFrame.ix[ ]**是基于标签和整数的切片技术。除了基于纯标签和基于整数，Pandas 还提供了一种混合方法，用于使用ix[]操作符选择和细分对象。ix[]是最通用的索引器，将支持[loc[]](https://www.geeksforgeeks.org/python-pandas-extracting-rows-using-loc/)和[iloc[]](https://www.geeksforgeeks.org/python-extracting-rows-using-pandas-iloc/)中的任何输入。
语法: DataFrame.ix[ ]
参数: 索引位置:整数或整数列表中行的索引位置。 索引标签:行索引标签的字符串或字符串列表
根据参数返回:数据帧或序列
Code #1:
# importing pandas package
import pandas as geek
# making data frame from csv file
data = geek.read_csv("https://media.geeksforgeeks.org/wp-content/uploads/nba.csv")
# Integer slicing
print("Slicing only rows(till index 4):")
x1 = data.ix[:4, ]
print(x1, "\n")
print("Slicing rows and columns(rows=4, col 1-4, excluding 4):")
x2 = data.ix[:4, 1:4]
print(x2)
输出:
代码#2:
# importing pandas package
import pandas as geek
# making data frame from csv file
data = geek.read_csv("nba.csv")
# Index slicing on Height column
print("After index slicing:")
x1 = data.ix[10:20, 'Height']
print(x1, "\n")
# Index slicing on Salary column
x2 = data.ix[10:20, 'Salary']
print(x2)
输出:
代码#3:
# importing pandas and numpy
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randn(10, 4),
columns = ['A', 'B', 'C', 'D'])
print("Original DataFrame: \n" , df)
# Integer slicing
print("\n Slicing only rows:")
print("--------------------------")
x1 = df.ix[:4, ]
print(x1)
print("\n Slicing rows and columns:")
print("----------------------------")
x2 = df.ix[:4, 1:3]
print(x2)
输出:
代码#4:
# importing pandas and numpy
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randn(10, 4),
columns = ['A', 'B', 'C', 'D'])
print("Original DataFrame: \n" , df)
# Integer slicing (printing all the rows of column 'A')
print("\n After index slicing (On 'A'):")
print("--------------------------")
x = df.ix[:, 'A']
print(x)
输出:
