merge

问题 I would like to know how if there exists any python function to merge two dictionary and combine all values that have a common key. I have found function to append two dict, to merge two dict but not to combine its values. Example: D1 = [{k1: v01}, {k3: v03}, {k4: v04},}], D2 = [{k1: v11}, {k2: v12}, {k4: v14},}], this should be the expected result: D3 = [ {k1: [v01, v11]}, {k2: [ v12]}, {K3: [v03 ]}, {k4: [v04, v14]}, ] 回答1: A solution, without importing anything: # First initialize data,

问题 Let's say I have a file with this content in master : Line 1 Line 2 Line 3 Line 4 Now say I create and checkout a new branch called test . In this branch I change the file to this: Line 1 Line 2 Line 3 Modified Line 4 and I commit this and switch back to master . In master I change the file to: Line 1 Line 2 Line 3 Line 4 Modified and I commit. Now if I merge branch test into master , I get a conflict. Why can't git auto resolve this, using the common ancestor? If I tell git to edit conflicts

问题 I have a situation where I would want to delete and shift cells in a pandas data frame basis some conditions. My data frame looks like this : Value_1 ID_1 Value_2 ID_2 Value_3 ID_3 A 1 D 1 G 1 B 1 E 2 H 1 C 1 F 2 I 3 C 1 F 2 H 1 Now I want to compare the following conditions: ID_2 and ID_3 should always be less than or equal to ID_1. If anyone of them is greater than ID_1 then that cell should be deleted and shifted with the next column cell The output should look like the following : Value_1

问题 I created a function that accepts multiple arguments of dictionaries, and returns a concatenated dictionary. I researched online for a while about concatenating a merging dictionaries and tested the interesting ones. They all resulted in updating the values (or overwriting them). My use case is passing in dictionaries where each key has a single value, and want a dictionary with the same or different keys, with a list of values for each key. That is my definition of what a so-called

问题 I am using IBM Rational Clear Case. Due the current world wide health situation, I am forced to work from home. The best way and may be the only one, when using Visual Studio, is working with a Web View (Please correct me if there is a better way) - I assume this is called CCRC (Clear Case Remote Client). It is similar to a Snapshot View but without constant connection to the Clear Case server at work (This statement is not entirely correct). When working with a snapshot view or for that

问题 I am trying to concatenate two dataframes, above and below. Not concatenate side-by-side. The dataframes contain the same data, however, in the first dataframe one column might have name "ObjectType" and in the second dataframe the column might have name "ObjectClass". When I do df_total = pandas.concat ([df0, df1]) the df_total will have two column names, one with "ObjectType" and another with "ObjectClass". In each of these two columns, half of the values will be "NaN". So I have to

问题 I am trying to concatenate two dataframes, above and below. Not concatenate side-by-side. The dataframes contain the same data, however, in the first dataframe one column might have name "ObjectType" and in the second dataframe the column might have name "ObjectClass". When I do df_total = pandas.concat ([df0, df1]) the df_total will have two column names, one with "ObjectType" and another with "ObjectClass". In each of these two columns, half of the values will be "NaN". So I have to

问题 I am trying to concatenate two dataframes, above and below. Not concatenate side-by-side. The dataframes contain the same data, however, in the first dataframe one column might have name "ObjectType" and in the second dataframe the column might have name "ObjectClass". When I do df_total = pandas.concat ([df0, df1]) the df_total will have two column names, one with "ObjectType" and another with "ObjectClass". In each of these two columns, half of the values will be "NaN". So I have to

问题 I am trying to concatenate two dataframes, above and below. Not concatenate side-by-side. The dataframes contain the same data, however, in the first dataframe one column might have name "ObjectType" and in the second dataframe the column might have name "ObjectClass". When I do df_total = pandas.concat ([df0, df1]) the df_total will have two column names, one with "ObjectType" and another with "ObjectClass". In each of these two columns, half of the values will be "NaN". So I have to

问题 Please suggest how to convert this teradata statement in MYSQL. As we know mysql doesn't support merge statement. Below 2 tables are also being used in select query and we have multiple primary key in each table. MERGE INTO XYZ USING ( SELECT ITRR.WORKFLOW_NAME WORKFLOW_NAME , ITRR.INSTANCE_NAME INSTANCE_NAME , MIN(ITRR.START_TIME) EARLIEST_START_TIME , ITRR.SUBJECT_AREA SUBJECT_AREA , 'INFORMATICA' PLATFORM_NAME FROM ABC IWRR , DEF ITRR WHERE IWRR.WORKFLOW_RUN_ID = ITRR.WORKFLOW_RUN_ID AND