- iterrows(): 将DataFrame迭代为(insex, Series)对。
- itertuples(): 将DataFrame迭代为元祖。
- iteritems():将DataFrame迭代为(列名, Series)对
现有如下DataFrame数据:
import pandas as pd
inp = [{'c1':10, 'c2':100}, {'c1':11, 'c2':110}, {'c1':12, 'c2':123}]
df = pd.DataFrame(inp)
print(df)
iterrows():
for date, row in df.iterrows():
print(date)
for date, row in df.iterrows():
print(row)
对于每一行,通过列名访问对应的元素
for date, row in df.iterrows():
print(row['c1'], row['c2'])
iteritems():
for date, row in df.iteritems():
print(date)
for date, row in df.iteritems():
print(row)
for date, row in df.iteritems():
print(row[0], row[1], row[2])
itertuples():
for row in df.itertuples():
print(row)
for row in df.itertuples():
print(getattr(row, 'c1'), getattr(row, 'c2'))
Tip:
intertuples相较于interrow的效率更高,遍历速度更快。因此在遍历dataframe的时候,可以优先使用intertuples。此外,当存带有时间的列名时,可以将其作为索引,则可以使用data.iloc[a_time:b_time],获取时间窗内的数据。
Original: https://blog.csdn.net/weixin_44439904/article/details/109569701
Author: 小路转角处
Title: iterrows(), iteritems(), itertuples()对dataframe进行遍历
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