pandas concat by id
pd.concat([s1, s2], keys=['s1', 's2'], ... names=['Series name', 'Row ID']) Series name Row ID s1 0 a 1 b s2 0 c 1 d dtype: object. Combine two DataFrame objects ... ,pd.concat([s1, s2], keys=['s1', 's2'], ... names=['Series name', 'Row ID']) Series name Row ID s1 0 a 1 b s2 0 c 1 d dtype: object. Combine two DataFrame objects ... ,pd.concat([s1, s2], keys=['s1', 's2'], ... names=['Series name', 'Row ID']) Series name Row ID s1 0 a 1 b s2 0 c 1 d dtype: object. Combine two DataFrame objects ... ,pd.concat([s1, s2], keys=['s1', 's2'], ... names=['Series name', 'Row ID']) Series name Row ID s1 0 a 1 b s2 0 c 1 d dtype: object. Combine two DataFrame objects ... ,pd.concat([s1, s2], keys=['s1', 's2'], ... names=['Series name', 'Row ID']) Series name Row ID s1 0 a 1 b s2 0 c 1 d dtype: object. Combine two DataFrame objects ... , #coding=utf-8 import pandas as pd import numpy as np # 讀取 data = pd.read_csv('student.csv') print(data) ''' Student ID name age gender 0 ..., 简单的合并可以通过Pandas中的concat函数来实现的。 ... keys=['s1', 's2'], ... names=['Series name', 'Row ID']) #新增列名Series name Row ID s1 ..., DataFrame(x.values, columns=x.columns)) .unstack() .sort_index(axis=1, level=1)) df.columns = ['}_}'.format(i, j) for i, j in df.columns] df ..., You could use groupby for that with groupby agg method and tolist method of Pandas Series: In [762]: df.groupby('id').agg(lambda x: x.tolist()) ...,Use merge : print (pd.merge(df1, df2, left_on='id', right_on='id1', how='left').drop('id1', axis=1)) id name count price rating 0 1 a 10 100.0 1.0 1 2 b 20 200.0 2.0 2 ...
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 pandas concat by id 相關參考資料
pandas.concat — pandas 0.24.2 documentation
pd.concat([s1, s2], keys=['s1', 's2'], ... names=['Series name', 'Row ID']) Series name Row ID s1 0 a 1 b s2 0 c 1 d dtype: object. Combine two DataFrame objects .... https://pandas.pydata.org pandas.concat — pandas 0.23.1 documentation
pd.concat([s1, s2], keys=['s1', 's2'], ... names=['Series name', 'Row ID']) Series name Row ID s1 0 a 1 b s2 0 c 1 d dtype: object. Combine two DataFrame objects .... https://pandas.pydata.org pandas.concat — pandas 0.23.4 documentation
pd.concat([s1, s2], keys=['s1', 's2'], ... names=['Series name', 'Row ID']) Series name Row ID s1 0 a 1 b s2 0 c 1 d dtype: object. Combine two DataFrame objects .... https://pandas.pydata.org pandas.concat — pandas 0.22.0 documentation
pd.concat([s1, s2], keys=['s1', 's2'], ... names=['Series name', 'Row ID']) Series name Row ID s1 0 a 1 b s2 0 c 1 d dtype: object. Combine two DataFrame objects .... https://pandas.pydata.org pandas.concat — pandas 0.21.1 documentation
pd.concat([s1, s2], keys=['s1', 's2'], ... names=['Series name', 'Row ID']) Series name Row ID s1 0 a 1 b s2 0 c 1 d dtype: object. Combine two DataFrame objects .... https://pandas.pydata.org [筆記] pandas 用法(2) 讀寫檔合併concat merge 圖表 - 陳雲濤的部落格
#coding=utf-8 import pandas as pd import numpy as np # 讀取 data = pd.read_csv('student.csv') print(data) ''' Student ID name age gender 0 ... http://violin-tao.blogspot.com concat、append、merge、join、combine_first - 知乎
简单的合并可以通过Pandas中的concat函数来实现的。 ... keys=['s1', 's2'], ... names=['Series name', 'Row ID']) #新增列名Series name Row ID s1 ... https://zhuanlan.zhihu.com Concatenate columns with same id Pandas DataFrame - Stack Overflow
DataFrame(x.values, columns=x.columns)) .unstack() .sort_index(axis=1, level=1)) df.columns = ['}_}'.format(i, j) for i, j in df.columns] df ... https://stackoverflow.com Concatenate rows of pandas DataFrame with same id - Stack Overflow
You could use groupby for that with groupby agg method and tolist method of Pandas Series: In [762]: df.groupby('id').agg(lambda x: x.tolist()) ... https://stackoverflow.com JOIN two dataframes on common column in python - Stack Overflow
Use merge : print (pd.merge(df1, df2, left_on='id', right_on='id1', how='left').drop('id1', axis=1)) id name count price rating 0 1 a 10 100.0 1.0 1 2 b 20 200.0 2.0 2&... https://stackoverflow.com |