Python dataFrame 行列遍历

转载：https://www.jb51.net/article/172623.htm

示例数据

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import pandas as pd

inp = [{'c1':10, 'c2':100}, {'c1':11, 'c2':110}, {'c1':12, 'c2':123}]

df = pd.DataFrame(inp)

print(df)

import pandas as pd inp = [{'c1':10, 'c2':100}, {'c1':11, 'c2':110}, {'c1':12, 'c2':123}] df = pd.DataFrame(inp) print(df)

按行遍历iterrows():

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for index, row in df.iterrows():

 print(index) # 输出每行的索引值

for index, row in df.iterrows(): print(index) # 输出每行的索引值

row[‘name']

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# 对于每一行，通过列名name访问对应的元素

for row in df.iterrows():

 print(row['c1'], row['c2']) # 输出每一行

# 对于每一行，通过列名name访问对应的元素 for row in df.iterrows(): print(row['c1'], row['c2']) # 输出每一行

按行遍历itertuples():

getattr(row, ‘name')

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for row in df.itertuples():

 print(getattr(row, 'c1'), getattr(row, 'c2')) # 输出每一行

for row in df.itertuples(): print(getattr(row, 'c1'), getattr(row, 'c2')) # 输出每一行

按列遍历iteritems():

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for index, row in df.iteritems():

 print(index) # 输出列名

for index, row in df.iteritems(): print(index) # 输出列名

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for row in df.iteritems():

 print(row[0], row[1], row[2]) # 输出各列

for row in df.iteritems(): print(row[0], row[1], row[2]) # 输出各列