I have a dataframe like: I’d like to create a newly scaled column in the dataframe called SIZE where SIZE is a number between 5 and 50. For Example: I’ve tried but got Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample. I’ve tried other things,
Tag: pandas
Pandas DataFrame Style for this condition
How can I use df.style for subsets of a DataFrame based on this given condition? I want to highlight the cells in which it is False. But make changes to df, not just df1 Have edited the question. It is different from the previous questions because they are only dealing with element-wise coloring. But I want to color based the
Pandas: reading Excel file starting from the row below that with a specific value
Say I have the following Excel file: I want to read the file in a dataframe making sure that I start to read it below the row where the Start value is. Attention: the Start value is not always located in the same row, so if I were to use: this would fail as skiprows needs to be fixed. Is
Highlight rows from a DataFrame based on values in a column in Python Pandas
I have been trying to highlight some rows in a pandas dataframe based on multiple conditions. I’m expecting that when a string in the target column match the criteria defined in the function, the entire row will be highlighted. I tried different combinations of the .style.apply method, but it kept giving me the following error: ValueError: style is not supported
pandas DataFrame: normalize one JSON column and merge with other columns
I have a pandas DataFrame containing one column with multiple JSON data items as list of dicts. I want to normalize the JSON column and duplicate the non-JSON columns: I want I can normalize JSON data using: but I don’t know how to join that back to the id column of the original DataFrame. Answer You can use concat with
Create Boxplot Grouped By Column
I have a Pandas DataFrame, df, that has a price column and a year column. I want to create a boxplot after grouping the rows based on their year. Here’s an example: So in this case, I’d want a boxplot for each of 2011, 2012, and 2013 based on their price column. I’ve looked into DataFrame.groupby but it produces a
How to remove timezone from a Timestamp column in a pandas dataframe
I read Pandas change timezone for forex DataFrame but I’d like to make the time column of my dataframe timezone naive for interoperability with an sqlite3 database. The data in my pandas dataframe is already converted to UTC data, but I do not want to have to maintain this UTC timezone information in the database. Given a sample of the
pandas Categorical error: “Cannot setitem on a Categorical with a new category, set the categories first”
I have the following df data frame in pandas: What I want to do is to order the data frame by the following days’ order: To do so, I used the following code: When I run the code, I get this error: I have not found enough documentation to resolve this. Can you help me? Thanks! Answer df[[‘weekday’]] returns a
How to show all columns’ names on a large pandas dataframe?
I have a dataframe that consist of hundreds of columns, and I need to see all column names. What I did: The output is: How do I show all columns, instead of a truncated list? Answer You can globally set printing options. I think this should work: Method 1: Method 2: This will allow you to see all column names
TypeError: ‘Series’ object is not callable when accessing dtypes of a dataframe
As it is [Duplicate], I have raised this to be removed. Kindly do not rollback. Answer There’s no ambiguity here. file is a dataframe, and dtypes is an attribute. When you access dtypes, a Series is returned: When you call df.dtypes(), you are effectively doing series = df.dtype; series() which is invalid, since series is an object (not a function,