熊猫| Python 中给定列的有限行选择
原文:https://www.geesforgeks.org/limited-row-selection-with-given-in-pandas-python/
熊猫中的方法如iloc[]、iat[] 一般用于从给定的数据帧中选择数据。在本文中，我们将学习如何在这些方法的帮助下选择给定列的有限行。
示例 1: 选择两列
# Import pandas package
import pandas as pd
# Define a dictionary containing employee data
data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj'],
'Age':[27, 24, 22, 32],
'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj'],
'Qualification':['Msc', 'MA', 'MCA', 'Phd']}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# select three rows and two columns
print(df.loc[1:3, ['Name', 'Qualification']])
输出:
Name Qualification
1 Princi MA
2 Gaurav MCA
3 Anuj Phd
示例 2: 首先按标签格式过滤行和选择列，然后选择所有列。
# Import pandas package
import pandas as pd
# Define a dictionary containing employee data
data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj'],
'Age':[27, 24, 22, 32],
'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj'],
'Qualification':['Msc', 'MA', 'MCA', 'Phd']
}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# .loc DataFrame method
# filtering rows and selecting columns by label format
# df.loc[rows, columns]
# row 1, all columns
print(df.loc[0, :] )
输出:
Address Delhi
Age 27
Name Jai
Qualification Msc
Name: 0, dtype: object
示例 3: 选择所有或部分列，使用 iloc 逐个选择。
# Import pandas package
import pandas as pd
# Define a dictionary containing employee data
data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj'],
'Age':[27, 24, 22, 32],
'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj'],
'Qualification':['Msc', 'MA', 'MCA', 'Phd']}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
# iloc[row slicing, column slicing]
print(df.iloc [0:2, 1:3] )
输出:
Age Name
0 27 Jai
1 24 Princi
