pandas 熊猫交叉加入没有共同的列
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pandas cross join no columns in common
提问by ostrokach
How would you perform a full outer joina cross joinof two dataframes with no columns in common using pandas?
您将如何使用 Pandas执行完全外连接和两个数据框的交叉连接，而没有共同的列？
In MySQL, you can simply do:
在 MySQL 中，您可以简单地执行以下操作：
SELECT *
FROM table_1
[CROSS] JOIN table_2;
But in pandas, doing:
但是在Pandas中，这样做：
df_1.merge(df_2, how='outer')
gives an error:
给出一个错误：
MergeError: No common columns to perform merge on
The best solution I have so far is using sqlite:
到目前为止我最好的解决方案是使用sqlite：
import sqlalchemy as sa
engine = sa.create_engine('sqlite:///tmp.db')
df_1.to_sql('df_1', engine)
df_2.to_sql('df_2', engine)
df = pd.read_sql_query('SELECT * FROM df_1 JOIN df_2', engine)
回答by jezrael
IIUC you need mergewith temporary columns tmpof both DataFrames:
IIUC 你需要两者的merge临时列：tmpDataFrames
import pandas as pd
df1 = pd.DataFrame({'fld1': ['x', 'y'],
'fld2': ['a', 'b1']})
df2 = pd.DataFrame({'fld3': ['y', 'x', 'y'],
'fld4': ['a', 'b1', 'c2']})
print df1
fld1 fld2
0 x a
1 y b1
print df2
fld3 fld4
0 y a
1 x b1
2 y c2
df1['tmp'] = 1
df2['tmp'] = 1
df = pd.merge(df1, df2, on=['tmp'])
df = df.drop('tmp', axis=1)
print df
fld1 fld2 fld3 fld4
0 x a y a
1 x a x b1
2 x a y c2
3 y b1 y a
4 y b1 x b1
5 y b1 y c2
回答by Istvan
Even in MySQL you have to specify which fields are you joining on.
即使在 MySQL 中，您也必须指定要加入的字段。
http://dev.mysql.com/doc/refman/5.7/en/join.html
http://dev.mysql.com/doc/refman/5.7/en/join.html
Example:
例子：
SELECT * FROM t1 LEFT JOIN t2 ON (t1.a = t2.a);
Same concept with Pandas:
与 Pandas 相同的概念：
Parameters:
right : DataFrame
how : {‘left', ‘right', ‘outer', ‘inner'}, default ‘inner'
left: use only keys from left frame (SQL: left outer join)
right: use only keys from right frame (SQL: right outer join)
outer: use union of keys from both frames (SQL: full outer join)
inner: use intersection of keys from both frames (SQL: inner join)
on : label or list
Field names to join on. Must be found in both DataFrames. If on is None and not merging on indexes, then it merges on the intersection of the columns by default.
left_on : label or list, or array-like
Field names to join on in left DataFrame. Can be a vector or list of vectors of the length of the DataFrame to use a particular vector as the join key instead of columns
right_on : label or list, or array-like
Field names to join on in right DataFrame or vector/list of vectors per left_on docs
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.merge.html
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.merge.html
