I need use pd.read_excel to process every sheet in one excel file. But in most cases,I did not know the sheet name. So I use this to judge how many sheet in excel: During the process,I found that the process is quite slow, So,can read_excel only read limited rows to improve the speed? I tried nrows but did not work..still
Tag: pandas
Reverse a get_dummies encoding in pandas
Column names are: ID,1,2,3,4,5,6,7,8,9. The col values are either 0 or 1 My dataframe looks like this: I want the column names in front of the ID where the value in a row is 1. The Dataframe i want should look like this: Please help me in this, Thanks in advance Answer set_index + stack, stack will dropna by default
How to plot aggregated by date pandas dataframe
I have this dataframe To aggregate payout_value by date I use: How do I plot (bar chart) dates on x-axis and aggregated payout sum on y axis? I tried using df.plot(x=’date’, y=’payout_value’,kind=”bar”) approach, but there is no ‘date’ column in df_daily dataframe, print(list(df_daily)) gives [(‘payout_value’, ‘sum’)] Answer you are almost there, use reset_index and plot your by df_daily
convert dataframe row to dict
I have datarame like the sample data below. I’m trying to convert one row from the dataframe in to a dict like the desired output below. But when I use to_dict I get the indice along with the column value. Does anyone know how to get convert the row to a dict like the desired output? Any tips greatly appreciated.
Set the format for pd.to_datetime
Hi already referred to this post but I could not get through my issue. I have a column in my CSV which is string and the sample values are below (note that the month and year positioning are sometimes reversed). What format do I need to set in my to_datetime? I tried all the below approaches I get the error
Save and export dtypes information of a python pandas dataframe
I have a pandas DataFrame named df. With df.dtypes I can print on screen: I want to save this information so that I can compare it with other data, type-cast things elsewhere, etc. I want to save it into to a local file, recover it elsewhere in another program where the data can’t go. But I’m not able to figure
Pandas: select cell value using pd.at with condition
I’d like to select specific cell values from a Pandas Dataframe. I want to filter out rows with specific values in column A, and then get the values from column B. From what I understand, the correct way to do this is to use df.at, so I’ve tried but this doesn’t work. I’ve also tried, as a hack, doesn’t work
How do I convert a Pandas dataframe to a PyTorch tensor?
How do I train a simple neural network with PyTorch on a pandas dataframe df? The column df[“Target”] is the target (e.g. labels) of the network. This doesn’t work: Answer I’m referring to the question in the title as you haven’t really specified anything else in the text, so just converting the DataFrame into a PyTorch tensor. Without information about
Pandas DataFrame column numerical integration
Currently I have a DataFrame as shown below: I would like to do the numerical integration of Current with TimeSec (∫Idt) for different Devices and collect the data into a new DataFrame as below: The problem is that the time interval is not even and the number of data for each device is not even as well. Answer Use some
Python Pandas finding column value based on multiple column values in same data frame
df: Now I want to get city name where “fruit= orange and price =5” is not working and giving error as: Versions used: Python 3.5 Answer You could create masks step-wise and see how they look like: