Python 使用panda中的interrows（）在两列中执行不完整的数学运算
嗨，我正在尝试减去数据帧的2列数据，并将其放入新的数据帧中。我正在interrows（）中使用for循环。但是，由于行的大小小于列，循环并没有完成所有计算。该列将在将来增加，因此我使用循环而不是列名。 是否有其他方法执行此计算Python 使用panda中的interrows（）在两列中执行不完整的数学运算,python,pandas,for-loop,subtraction,Python,Pandas,For Loop,Subtraction,嗨，我正在尝试减去数据帧的2列数据，并将其放入新的数据帧中。我正在interrows（）中使用for循环。但是，由于行的大小小于列，循环并没有完成所有计算。该列将在将来增加，因此我使用循环而不是列名。 是否有其他方法执行此计算 name col1 col2 col3 col4 col5 col6 col7 col8 John 0 23 0 1 4 1 5 23 1
name col1 col2 col3 col4 col5 col6 col7 col8
John 0 23 0 1 4 1 5 23
1 victor 1 4 5 2 1 4 2 15
2 Alida 1 1 2 6 0 2 14 2
3 Natalie 0 1 1 4 2 3 4 4
4 Morman 3 3 1 0 5 2 0 1
for label, row in df.iterrows():
df2.iloc[:,[label+2]]=df.iloc[:,[label+2]].values-df.iloc[:,[label+1]].values
是否仍要运行循环，直到循环遍历所有列？您可以对数据帧使用
diffdf.set_index('name').diff(axis=1)
这将您的名称列设置为行索引，然后从下一列中减去每一列。正如您所提到的，输出中将少一列，因此结果col1将是NaNs。您可以对数据帧使用
diffdf.set_index('name').diff(axis=1)
这将您的名称列设置为行索引，然后从下一列中减去每一列。正如您所提到的，输出中将少一列，因此结果col1将是NaNs。如果要减去两个特定的列，请使用以下方法：
import numpy as np
import pandas as pd
data = {"name":["john","victor","alida","natalie","morman"],"col1":[0,1,2,3,4],"col2":[5,6,7,8,9],"col3":[0,1,2,3,4],"col4":[5,6,7,8,9],"col5":[0,1,2,3,4],"col6":[5,6,7,8,9],"col7":[0,1,2,3,4]}
df = pd.DataFrame(data=data)
print(df)
new_df = pd.DataFrame()
new_df["new_col"] = df["col1"] - df["col2"]
print(new_df)
cols = df.columns
for i in range(2,len(cols)-1):
new_df["new_" + cols[i]] = df[cols[i]]-df[cols[i-1]]
print(new_df)
import numpy as np
import pandas as pd
data = {"name":["john","victor","alida","natalie","morman"],"col1":[0,1,2,3,4],"col2":[5,6,7,8,9],"col3":[0,1,2,3,4],"col4":[5,6,7,8,9],"col5":[0,1,2,3,4],"col6":[5,6,7,8,9],"col7":[0,1,2,3,4]}
df = pd.DataFrame(data=data)
print(df)
new_df = pd.DataFrame()
new_df["new_col"] = df["col1"] - df["col2"]
print(new_df)
cols = df.columns
for i in range(2,len(cols)-1):
new_df["new_" + cols[i]] = df[cols[i]]-df[cols[i-1]]
print(new_df)
如果要减去两个specefic列，请使用col1和col2：
import numpy as np
import pandas as pd
data = {"name":["john","victor","alida","natalie","morman"],"col1":[0,1,2,3,4],"col2":[5,6,7,8,9],"col3":[0,1,2,3,4],"col4":[5,6,7,8,9],"col5":[0,1,2,3,4],"col6":[5,6,7,8,9],"col7":[0,1,2,3,4]}
df = pd.DataFrame(data=data)
print(df)
new_df = pd.DataFrame()
new_df["new_col"] = df["col1"] - df["col2"]
print(new_df)
cols = df.columns
for i in range(2,len(cols)-1):
new_df["new_" + cols[i]] = df[cols[i]]-df[cols[i-1]]
print(new_df)
import numpy as np
import pandas as pd
data = {"name":["john","victor","alida","natalie","morman"],"col1":[0,1,2,3,4],"col2":[5,6,7,8,9],"col3":[0,1,2,3,4],"col4":[5,6,7,8,9],"col5":[0,1,2,3,4],"col6":[5,6,7,8,9],"col7":[0,1,2,3,4]}
df = pd.DataFrame(data=data)
print(df)
new_df = pd.DataFrame()
new_df["new_col"] = df["col1"] - df["col2"]
print(new_df)
cols = df.columns
for i in range(2,len(cols)-1):
new_df["new_" + cols[i]] = df[cols[i]]-df[cols[i-1]]
print(new_df)
你能解释一下你希望看到的输出是什么吗？此外，当您使用
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