Category "pandas"

pandas scraping html tables

There is an HTML file of tables. There are about 100 of them, and they all often have the same values. The values in the second and first column of all tables a

Python Rolling sum for 32 bit vs 64 bit

I am getting strange results when doing rollingSum for 64 bit vs 32 bit precision. Please see the code for display 1 vs 2. Display 1 shows the right rolling sum

Why are all my variables objects instead of numerical values (int,float) when uploaded?

I just started so that might be stupid, but I have following problem: I created a .csv-file for some basic data description. However, although they are all nume

Utilizing multiple processors to load large number of files for pandas (python)

I need to load hundreds or thousands of JSON files into a big pandas dataframe. My current solution using a for loop to iterate the directory is slow and is not

Groupby hours +/- some integer of additional hours

I have a data frame consisting of some columns, where the index is datetime, i.e. it looks something like: df = col1 col2

Make a dataframe avaliable until it's update [duplicate]

I have a Flask application with reads a dataframe and provide it in a service. The problem is that I need to update it (only a reading from s

Getting error 'NoneType' object has no attribute 'read' in python for image processing image_dataframe['image']

I am working on image classification using CNN. I am using below source code for that task. I am stuck with this error : AttributeError: 'NoneType' object has

Split dataframe column at specific words

One column in my dataframe is a long string. I want to split out portions of the string into its own column based on a few different words. What would be the be

How to reassign values in column by condition in dataframe?

df = pd.DataFrame([["A", "AA", "AAA", "found"], ["A", "AB", "ABA", "not found"], ["A", "AB", "ABB", "not found"],

Make a dataframe avaliable until it's update [duplicate]

I have a Flask application with reads a dataframe and provide it in a service. The problem is that I need to update it (only a reading from s

KeyError while reading a CSV file in Python

I am trying to plot the fall of an object (an optical fork to be precise) as a function of time in order to verify that the law of gravity is indeed 9.81. The d

Python: Reading a Windows generated csv with carriage return in column

I'm working on a Python program that needs to read csv files that are produced on a Windows 2012 server machine. The aim of the Python code is to give a min/max

How to exclude weekends and holidays from finding the difference between two dates in python

I need to find the difference between 2 dates where certain end dates are blank. I am need to exclude the weekends, as well as the holidays when calculating the

reading data-frame with missing values

I am trying to read some df with few columns and few rows where in some rows data are missing. For example df looks like this, also elements of the df are separ

Pandas MultiIndex match on one index level

I have a pandas MultiIndex object where the first level is a regular increasing index of ints, and the second level contains other integers that may or may not

Read entire row if a specific column has background color in excel sheet using Python

I have an excel sheet which has few columns with background color. I need to fetch all rows which has background color in column B. I tried with styleframe but

How to plot multiple chart on one figure and combine with another?

# Create an axes object axes = plt.gca() # pass the axes object to plot function df.plot(kind='line', x='鄉鎮別', y='男', ax=axes,figs

How to plot multiple chart on one figure and combine with another?

# Create an axes object axes = plt.gca() # pass the axes object to plot function df.plot(kind='line', x='鄉鎮別', y='男', ax=axes,figs

How to plot multiple chart on one figure and combine with another?

# Create an axes object axes = plt.gca() # pass the axes object to plot function df.plot(kind='line', x='鄉鎮別', y='男', ax=axes,figs

Pandas: imputing descriptive stats using a groupby with a variable

I have a data frame like this: input_df = pd.DataFrame({"sex": ["M", "F", "F", "M", "M"], "Class": [1, 2, 2, 1, 1], "Age":[40, 30, 30, 50, NaN]}) What I want t