如何在 DataFrame 中获取列名和行名?
在分析通常非常庞大的真实数据集时,我们可能需要获取行或索引名称和列名称才能执行某些操作。
注意:要下载以下示例中使用的nba数据集,请单击此处
在 Pandas 数据框中获取行名
首先,让我们用 nba.csv 创建一个简单的数据框
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# calling head() method
# storing in new variable
data_top = data.head(10)
# display
data_top
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# calling head() method
# storing in new variable
data_top = data.head()
# iterating the columns
for row in data_top.index:
print(row, end = " ")
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# calling head() method
# storing in new variable
data_top = data.head()
# list(data_top) or
list(data_top.index)
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# calling head() method
# storing in new variable
data_top = data.head()
list(data_top.index.values)
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# calling head() method
# storing in new variable
data_top = data.head()
list(data_top.index.values.tolist())
Python3
# iterate the indices and print each one
for row in data.index:
print(row, end = " ")
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
row_count = 0
# iterating over indices
for col in data.index:
row_count += 1
# print the row count
print(row_count)
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# iterating the columns
for col in data.columns:
print(col)
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# list(data) or
list(data.columns)
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
list(data.columns.values)
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
list(data.columns.values.tolist())
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# using sorted() method
sorted(data)
输出:
现在让我们尝试从上面的数据集中获取行名。
方法#1:简单地迭代索引
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# calling head() method
# storing in new variable
data_top = data.head()
# iterating the columns
for row in data_top.index:
print(row, end = " ")
输出:
0 1 2 3 4 5 6 7 8 9
方法#2:使用带有数据框对象的行
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# calling head() method
# storing in new variable
data_top = data.head()
# list(data_top) or
list(data_top.index)
输出:
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
方法#3: index.values 方法返回一个索引数组。
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# calling head() method
# storing in new variable
data_top = data.head()
list(data_top.index.values)
输出:
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
方法#4:使用给定索引列表的值的 tolist() 方法。
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# calling head() method
# storing in new variable
data_top = data.head()
list(data_top.index.values.tolist())
输出:
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
方法#5:计算数据框中的行数
由于我们使用 head() 方法仅加载了数据帧的前 10 行,因此让我们首先验证总行数。
Python3
# iterate the indices and print each one
for row in data.index:
print(row, end = " ")
输出:
现在,让我们打印索引的总数。
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
row_count = 0
# iterating over indices
for col in data.index:
row_count += 1
# print the row count
print(row_count)
输出:
458
在 Pandas 数据框中获取列名
现在让我们尝试从 nba.csv 数据集中获取列名。
方法#1:简单地遍历列
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# iterating the columns
for col in data.columns:
print(col)
输出:
方法#2:使用带有数据框对象的列
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# list(data) or
list(data.columns)
输出:
方法#3: column.values 方法返回一个索引数组。
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
list(data.columns.values)
输出:
方法 #4:使用 tolist() 方法和给定列列表的值。
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
list(data.columns.values.tolist())
输出:
方法 #5:使用 sorted() 方法
Sorted() 方法将返回按字母顺序排序的列列表。
Python3
# Import pandas package
import pandas as pd
# making data frame
data = pd.read_csv("nba.csv")
# using sorted() method
sorted(data)
输出: