2024 Get index of matching row pandas

Get index of matching row pandas

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August undefined, 2024

WebOct 3, 2024 · It can be solved using the Index + Match functionality of excel. What shall be the best way to replicate it in Pandas. Desired Output: add a new column 'price' dates currency amount price 02-Jan aud 100 0.73 03-Jan gbp 330 1.4 30-Jan eur 500 1.18 python pandas dataframe lookup data-munging Share Improve this question Follow WebSep 13, 2024 · 4 Answers Sorted by: 15 Use last_valid_index: s = pd.Series ( [False, False, True, True, False, False]) s.where (s).last_valid_index () Output: 3 Using @user3483203 example s = pd.Series ( ['dog', 'cat', 'fish', 'cat', 'dog', 'horse'], index= [*'abcdef']) s.where (s=='cat').last_valid_index () Output 'd' Share Follow edited Feb 12, 2024 at 18:51

python - Index match in Pandas? - Stack Overflow

WebNov 18, 2016 · Get first row where A > 3 (returns row 2) Get first row where A > 4 AND B > 3 (returns row 4) Get first row where A > 3 AND (B > 3 OR C > 2) (returns row 2) But, if there isn't any row that fulfil the specific criteria, then I want to get the first one after I just sort it descending by A (or other cases by B, C etc) WebAug 20, 2013 · If you use numpy, you can get an array of the indecies that your value is found: import numpy as np import pandas as pd myseries = pd.Series ( [1,4,0,7,5], index= [0,1,2,3,4]) np.where (myseries == 7) This returns a one element tuple containing an array of the indecies where 7 is the value in myseries: (array ( [3], dtype=int64),) symptoms iodine deficiency women

python - Efficiently find matching rows (based on …

WebJul 29, 2014 · I have extracted 10 random rows from the source data (using Stata) and now I want to write a test see if those rows are in the DataFrame in my test suite. As a small example. np.random.seed (2) raw_data = … Web5. Select rows where multiple columns are in list_of_values. If you want to filter using both (or multiple) columns, there's any() and all() to reduce columns (axis=1) depending on the need. Select rows where at least one of A or B is in list_of_values: df[df[['A','B']].isin(list_of_values).any(1)] df.query("A in @list_of_values or B in @list ... WebAlternatively, you can first filter the dataframe with the given condition (for example, where column matches a specific value) and then get the index of the resulting filtered dataframe. The following is the syntax. # get index … symptom sinus headache

python - Index - Match using Pandas - Stack Overflow

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Web6 hours ago · My dataframe has several prediction variable columns and a target (event) column. The events are either 1 (the event occurred) or 0 (no event). There could be consecutive events that make the target column 1 for the consecutive timestamp. I want to shift (backward) all rows in the dataframe when an event occurs and delete all rows … WebNov 30, 2024 · Get Indices of Rows Containing Integers/Floats in Pandas. The pandas.DataFrame.loc function can access rows and columns by its labels/names. It is … symptoms involving throat icd 10WebLittle sum up for searching by row: This can be useful if you don't know the column values or if columns have non-numeric values. if u want get index number as integer u can also do: item = df [4:5].index.item () print (item) 4. symptoms intestinal pneumatosis

"WebApr 9, 2024 · 1) In each iteration, ser is a Series that hold the values of each single row and hence the Series name is the row index (by default). So, when we call ser.name we actually ask for the Series name (aka the row number). 2) And why the +1, because the indexing of your list [1, 3, 5] starts at 1 while the indexing of the rows in a DataFrame starts ... " - Get index of matching row pandas

Get index of matching row pandas

python - Tweaking Pandas dataframe to train a regression …

Webdf2.apply(lambda row: pd.Index(df1.dta).get_loc(row.dtb), axis=1) Share. Improve this answer. Follow answered Feb 23, 2024 at 22:14. godot godot. 1,470 13 ... Python/pandas: Find matching values from two dataframes and return third value. 0. Remove rows that have common index/indices from two dataframes. WebNov 28, 2024 · To get the highlighted value 1.75 simply df2.loc [df2 ['Country']=='B', 3] So generalizing the above and using country-weight key pairs from df1: cost = [] for i in range (df1.shape [0]): country = df1.loc [i, 'Country'] weight = df1.loc [i, 'Weight'] cost.append (df2.loc [df2 ['Country']==country, weight] df1 ['Cost'] = cost Or much better:

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WebJul 14, 2014 · import pandas as pd dfB = pd.DataFrame ( {'X': [1,2,3],'Y': [1,2,3], 'Time': [10,20,30]}) dfA = pd.DataFrame ( {'X': [1,1,2,2,2,3],'Y': [1,1,2,2,2,3], 'ONSET_TIME': [5,7,9,16,22,28],'COLOR': ['Red','Blue','Blue','red','Green','Orange']}) #create one single table mergeDf = pd.merge (dfA, dfB, left_on = ['X','Y'], right_on = ['X','Y']) #remove rows … Web3 hours ago · Thanks for the help and sorry if there is anything wrong with my question. This function: shifted_df.index = pd.Index (range (2, len (shifted_df) + 2)) is the first one which as actually changing the index of my dataframe but it just overwrites the given index with the numbers 2 to len (shifted_df) pandas. dataframe.

WebFor example, if you want to get the row indexes where NumCol value is greater than 0.5, BoolCol value is True and the product of NumCol and BoolCol values is greater than 0, you can do so by evaluating an expression via eval() and call pipe() on the result to … WebIn this example, I’ll illustrate how to find the indices of all rows where the column x2 contains the value 5. For this, we can use the index attribute of our pandas DataFrame in …

WebNov 2, 2024 · Now let’s try to get the row name from above dataset. Method #1: Simply iterate over indices. Python3. import pandas as pd. data = pd.read_csv ("nba.csv") data_top = data.head () for row in data_top.index: print(row, end = " ") Output: WebMay 26, 2024 · A value is trying to be set on a copy of a slice from a DataFrame.Try using .loc [row_indexer,col_indexer] = value instead but when I try to fix that with rdf1.loc [rdf1 ['Open']] = rdf1.Date.map (intradayho.set_index ('Date') ['Open'].to_dict ()) I get an error: KeyError: "None of [Float64Index ( [nan, nan], dtype='float64')] are in the [index]"

WebSep 22, 2024 · With an index, each lookup is O (1) on average, whereas westcoast ['state']=='Oregon' requires O (n) comparisons. Of course, building the index is also O (n), so you would need to do many lookups for this to pay off. At the same time, once you have state_capitals the syntax is simple and dict-like.

WebMay 31, 2016 · First, use reset_index on B to make the index a new column in the dataframe. Then use an inner join to combine the two dataframes together using the merge function. Make sure you disable sorting during the join operation. The index column in the new dataframe will have what you want. symptoms isqWeb2 days ago · I would like to compare a list in a pandas column with another normal list and find the match value and put it in another column. I have a list of terms and would like to find whether there is a match for the particular word symptoms in women for strokeWebDec 19, 2016 · In [1]: a[a['c2'] == 1].index[0] In [2]: a[a['c1'] > 7].index[0] Out[1]: 0 Out[2]: 4 Where the query returns more than one row, the additional index results can be accessed by specifying the desired index, e.g. .index[n] thai diner 2 carytown richmond vaWebSep 4, 2015 · Pandas: compare two columns and return matched rows. I have two dataframes with multiple columns. I would like to compare df1 ['postcode'] and df2 ['pcd'] and build a new df based on the matched values of these two columns. Note- the length of the two columns I want to match is not the same. df1 postcode brand 1 znuee soony 2 eusjk … symptoms iodine deficiencyWebID Name Number DOB Salary 4 DDD 1237 05-09-2000 540000. I've tried all possible ways like. pd.merge (df1, df2, left_on= [ID,Name],right_on= [ID,Name], how='inner') and this produces all the unique keys that are in both the data frames. But this also produces non matching records. But I'm getting this as my result : ID Name Number DOB Salary 1 ... symptoms in utiWebIndexing and selecting data #. Indexing and selecting data. #. The axis labeling information in pandas objects serves many purposes: Identifies data (i.e. provides metadata) using known indicators, important for analysis, visualization, and interactive console display. Enables automatic and explicit data alignment. thai diner allentown symptom sinus infection