duplicates

问题 This is the continuation of the OP1 and OP2. Specifically, the objective is to remove duplicates if more than one dict has the same content for the key paper_title . However, the line throw an error if there inconsistency in the way the list is imputed, such that if there is a combination of dict and str TypeError: string indices must be integers The complete code which generates the aforementioned error is as below: - from itertools import groupby def extract_secondary(): # test_list = [{

问题 I have a huge DataFrame , where some columns have the same names. When I try to pick a column that exists twice, (eg del df['col name'] or df2=df['col name'] ) I get an error. What can I do? 回答1: You can adress columns by index: >>> df = pd.DataFrame([[1,2],[3,4],[5,6]], columns=['a','a']) >>> df a a 0 1 2 1 3 4 2 5 6 >>> df.iloc[:,0] 0 1 1 3 2 5 Or you can rename columns, like >>> df.columns = ['a','b'] >>> df a b 0 1 2 1 3 4 2 5 6 回答2: Another solution: def remove_dup_columns(frame): keep

问题 I have the following script to return search results of linked pages. I need to filter out the duplicates of the alias pages, as well as sort the results alphabetically. Currently, it returns both main page and alias page and does not sort them. <script runat="server"> bool hasDegree; bool hasCertificate; bool hasLetter; protected override void OnInit(EventArgs e) { base.OnInit(e); hasDegree = ValidationHelper.GetBoolean(CMS.DocumentEngine.DocumentHelper .GetDocuments("FCC.Credential").Path

问题 Lets say I have 9 rows of records. Each 3 rows have the same value. For instance: Mike Mike Mike John John John Ryan Ryan Ryan Is there a way I can search for similarities of these records? For example spelling mistakes, additional characters, missing characters, etc. So, for example, the correct version is Mike , but there might be a record down in the list with value Mke which is incorrect (spelling mistake). How can I find this and replace it with the correct one? The above example is

问题 Lets say I have 9 rows of records. Each 3 rows have the same value. For instance: Mike Mike Mike John John John Ryan Ryan Ryan Is there a way I can search for similarities of these records? For example spelling mistakes, additional characters, missing characters, etc. So, for example, the correct version is Mike , but there might be a record down in the list with value Mke which is incorrect (spelling mistake). How can I find this and replace it with the correct one? The above example is

问题 I'm creating coordinate plane Three in a row game so I have to find out if there are three numbers of the same value in the array BUT WITHOUT sorting array because the array represents the x-coordinates of the points added to the coordinate plane during the game... For example, let's say that I've added 6 points to the coordinate plane with x-coordinates stored in next array: var arr = [2,2,3,2,7,3]; I need the loop that will count only the occurrences of the value 2 because the number 2

问题 I'm creating coordinate plane Three in a row game so I have to find out if there are three numbers of the same value in the array BUT WITHOUT sorting array because the array represents the x-coordinates of the points added to the coordinate plane during the game... For example, let's say that I've added 6 points to the coordinate plane with x-coordinates stored in next array: var arr = [2,2,3,2,7,3]; I need the loop that will count only the occurrences of the value 2 because the number 2

问题 I have a Pandas DataFrame that has a column that is basically a foreign key, as below: Index | f_key | values 0 | 1 | red 1 | 2 | blue 2 | 1 | green 3 | 2 | yellow 4 | 3 | orange 5 | 1 | violet What I would like is to add a column that labels the repeated foreign keys sequentially, as in "dup_number" below: Index | dup_number | f_key | values 0 | 1 | 1 | red 1 | 1 | 2 | blue 2 | 2 | 1 | green 3 | 2 | 2 | yellow 4 | 1 | 3 | orange 5 | 3 | 1 | violet The rows can be reordered if needed, I just

问题 These are the key/values in JSON [ { "country":"First", "coupon":["1"] }, { "country":"First", "coupon":["10"] }, { "country":"First", "coupon":["12"] }, { "country":"Second", "coupon":"2" }, { "country":"third", "coupon":"3" }, { "country":"fourth", "coupon":"4" }, { "country":"fifth", "coupon":"5" } ] I sorted out the duplicates in JSON and displayed on dropdown var sortedCountries = []; if (sortedCountries.indexOf(value.country) == -1) { $('#sel').append('<option value="' + value.coupon +

问题 I'm using the code below to compare two dataframe and identified differences. However, I'm noticing that I'm simply overwriting my values ( combine_df ). My goal is to Flag if row values are different. But not sure what I"m doing wrong. #Find the overlapping columns in order to compare their values cols = set(module_df.columns) & (set(expected_df.columns)) #create filter dataframes only with the overlapping columns filter_module = expected_df.select(list(cols)) filter_expected = expected_df