pandas

问题 I'd like to know if it's possible to display a pandas dataframe in VS Code while debugging (first picture) as it is displayed in PyCharm (second picture) ? Thanks for any help. df print in vs code: df print in pycharm: 回答1: As of the January 2021 release of the python extension, you can now view pandas dataframes with the built-in data viewer when debugging native python programs. When the program is halted at a breakpoint, right-click the dataframe variable in the variables list and select

问题 I would like to merge nine Pandas dataframes together into a single dataframe, doing a join on two columns, controlling the column names. Is this possible? I have nine datasets. All of them have the following columns: org, name, items,spend I want to join them into a single dataframe with the following columns: org, name, items_df1, spend_df1, items_df2, spend_df2, items_df3... I've been reading the documentation on merging and joining. I can currently merge two datasets together like this:

问题 I am trying to insert data in a Pandas DataFrame into an existing Django model, Agency , that uses a SQLite backend. However, following the answers on How to write a Pandas Dataframe to Django model and Saving a Pandas DataFrame to a Django Model leads to the whole SQLite table being replaced and breaking the Django code. Specifically, it is the Django auto-generated id primary key column that is replaced by index that causes the errors when rendering templates ( no such column: agency.id ).

问题 Trying to create a new column in the netc df but i get the warning netc["DeltaAMPP"] = netc.LOAD_AM - netc.VPP12_AM C:\Anaconda\lib\site-packages\ipykernel\__main__.py:1: SettingWithCopyWarning: 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 whats the proper way to create a field in the newer version of Pandas to avoid getting the warning? pd.__version__ Out[45]: u'0.19.2+0.g825876c.dirty' 回答1: As it says in the error

问题 When you merge two indexed dataframes on certain values using 'outer' merge, python/pandas automatically adds Null (NaN) values to the fields it could not match on. This is normal behaviour, but it changes the data type and you have to restate what data types the columns should have. fillna() or dropna() do not seem to preserve data types immediately after the merge. Do I need a table structure in place? Typically I would run numpy np.where(field.isnull() etc) but that means running for all

问题 When you merge two indexed dataframes on certain values using 'outer' merge, python/pandas automatically adds Null (NaN) values to the fields it could not match on. This is normal behaviour, but it changes the data type and you have to restate what data types the columns should have. fillna() or dropna() do not seem to preserve data types immediately after the merge. Do I need a table structure in place? Typically I would run numpy np.where(field.isnull() etc) but that means running for all

问题 I am currently working on implement the C# version of a Gurobi linear program model that was earlier built in Python. I have a number of CSV files from which I was importing the data and creating pandas dataframes, and I was fetching columns from those dataframes to create variables that I was using in my Linear Program. The python code for creating the variables using dataframes is as follows: dataPath = "C:/Users/XYZ/Desktop/LinearProgramming/TestData" routeData = pd.DataFrame.from_csv(os

问题 I am currently working on implement the C# version of a Gurobi linear program model that was earlier built in Python. I have a number of CSV files from which I was importing the data and creating pandas dataframes, and I was fetching columns from those dataframes to create variables that I was using in my Linear Program. The python code for creating the variables using dataframes is as follows: dataPath = "C:/Users/XYZ/Desktop/LinearProgramming/TestData" routeData = pd.DataFrame.from_csv(os

问题 I was defining a function Heiken Ashi which is one of the popular chart type in Technical Analysis. I was writing a function on it using Pandas but finding little difficulty. This is how Heiken Ashi [HA] looks like- Heikin-Ashi Candle Calculations HA_Close = (Open + High + Low + Close) / 4 HA_Open = (previous HA_Open + previous HA_Close) / 2 HA_Low = minimum of Low, HA_Open, and HA_Close HA_High = maximum of High, HA_Open, and HA_Close Heikin-Ashi Calculations on First Run HA_Close = (Open +

问题 I was defining a function Heiken Ashi which is one of the popular chart type in Technical Analysis. I was writing a function on it using Pandas but finding little difficulty. This is how Heiken Ashi [HA] looks like- Heikin-Ashi Candle Calculations HA_Close = (Open + High + Low + Close) / 4 HA_Open = (previous HA_Open + previous HA_Close) / 2 HA_Low = minimum of Low, HA_Open, and HA_Close HA_High = maximum of High, HA_Open, and HA_Close Heikin-Ashi Calculations on First Run HA_Close = (Open +