【个人作业】在 Python 中查找 Pandas dataframe中元素的位置_dataframe查找值所在位置

简介

在本文中，我们将了解如何使用用户定义的函数来查找dataframe中元素的位置。让我们首先使用列表字典创建一个简单的dataframe，假设列名是：“名称”、“年龄”、“城市”和“区域”。

import pandas as pd

students = [('Ankit', 23, 'Delhi', 'A'),
            ('Swapnil', 22, 'Delhi', 'B'),
            ('Aman', 22, 'Dehradun', 'A'),
            ('Jiten', 22, 'Delhi', 'A'),
            ('Jeet', 21, 'Mumbai', 'B')
            ]

df = pd.DataFrame(students, columns =['Name', 'Age', 'City', 'Section'])
df
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输出结果：

示例 1：在dataframe中查找元素的位置。

students = [('Ankit', 23, 'Delhi', 'A'),
            ('Swapnil', 22, 'Delhi', 'B'),
            ('Aman', 22, 'Dehradun', 'A'),
            ('Jiten', 22, 'Delhi', 'A'),
            ('Jeet', 21, 'Mumbai', 'B')
            ]
# Creating Dataframe object

df = pd.DataFrame(students, columns =['Name', 'Age', 'City', 'Section'])

# This function will return a list of
# positions where element exists
# in the dataframe.
def getIndexes(dfObj, value):

    # Empty list
    listOfPos = []

    # isin() method will return a dataframe with
    # boolean values, True at the positions   
    # where element exists

    result = dfObj.isin([value])

    # any() method will return
    # a boolean series

    seriesObj = result.any()
    columnNames = list(seriesObj[seriesObj == True].index)

    for col in columnNames:
        rows = list(result[col][result[col] == True].index)
        for row in rows:
            listOfPos.append((row, col))
    return listOfPos

# Calling getIndexes() function to get
# the index positions of all occurrences
# of 22 in the dataframe

listOfPositions = getIndexes(df, 22)

print('Index positions of 22 in Dataframe : ')

# Printing the position

for i in range(len(listOfPositions)):
    print( listOfPositions[i])
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结果输出：

现在让我们了解函数 getIndexes() 的工作原理。 isin()、dataframe/series.any() 接受值并返回一个带有布尔值的dataframe。这个布尔dataframe的大小与第一个原始dataframe的大小相似。在dataframe中存在给定元素的位置，该值为 True，否则为 False。然后找到包含元素 22 的列的名称。我们可以通过在包含 True 的布尔dataframe中获取列的名称来完成此操作。现在在布尔dataframe中，我们遍历每个选定的列，对于每一列，我们找到 True 的行。现在，这些 True 存在的列名和行索引的组合是数据帧中 22 的索引位置。这就是 getIndexes() 如何找到给定元素的准确索引位置 & amp;以(行，列)元组的形式存储每个位置。最后，它返回一个元组列表，表示其在数据帧中的索引位置。

示例 2：在数据帧中查找多个元素的位置。

# Import pandas library
import pandas as pd

# List of tuples
students = [('Ankit', 23, 'Delhi', 'A'),
            ('Swapnil', 22, 'Delhi', 'B'),
            ('Aman', 22, 'Dehradun', 'A'),
            ('Jiten', 22, 'Delhi', 'A'),
            ('Jeet', 21, 'Mumbai', 'B')
            ]
# Creating Dataframe object
df = pd.DataFrame(students, columns =['Name', 'Age', 'City', 'Section'])

# This function will return a
# list of positions where
# element exists in dataframe
def getIndexes(dfObj, value):
    # Empty list
    listOfPos = []

    # isin() method will return a dataframe with
    # boolean values, True at the positions   
    # where element exists

    result = dfObj.isin([value])

    # any() method will return
    # a boolean series
    seriesObj = result.any()

     # Get list of columns where element exists
    columnNames = list(seriesObj[seriesObj == True].index)

    # Iterate over the list of columns and
    # extract the row index where element exists
    for col in columnNames:
        rows = list(result[col][result[col] == True].index)
         for row in rows:
            listOfPos.append((row, col))
    # This list contains a list tuples with
    # the index of element in the dataframe
    return listOfPos

# Create a list which contains all the elements
# whose index position you need to find

listOfElems = [22, 'Delhi']

# Using dictionary comprehension to find
# index positions of multiple elements
# in dataframe

dictOfPos = {elem: getIndexes(df, elem) for elem in listOfElems}
print('Position of given elements in Dataframe are : ')

# Looping through key, value pairs
# in the dictionary
for key, value in dictOfPos.items():
    print(key, ' : ', value)
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结果输出：

文章转载自： https://verytoolz.com/blog/591c04080a/