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I am able to convert a csv file to pandas DataFormat and able to print out the table, as seen below. However, when I try to print out the Height column I get an error. How can I fix this?
import pandas as pd
df = pd.read_csv('/path../NavieBayes.csv')
print df #this prints out as seen below
print df.Height #this gives me the "AttributeError: 'DataFrame' object has no attribute 'Height'
Height Weight Classifer
0 70.0 180 Adult
1 58.0 109 Adult
2 59.0 111 Adult
3 60.0 113 Adult
4 61.0 115 Adult
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If you try to call concat() on a DataFrame object, you will raise the AttributeError: 'DataFrame' object has no attribute 'concat'. You have to pass the columns to concatenate to pandas. concat() and define the axis to concatenate along.
the reason of " 'DataFrame' object has no attribute 'Number'/'Close'/or any col name " is because you are looking at the col name and it seems to be "Number" but in reality it is " Number" or "Number " , that extra space is because in the excel sheet col name is written in that format.
DataFrame is a 2-dimensional labeled data structure with columns of potentially different types. You can think of it like a spreadsheet or SQL table, or a dict of Series objects. It is generally the most commonly used pandas object.
The long answer is the size limit for pandas DataFrames is 100 gigabytes (GB) of memory instead of a set number of cells.
I have run into a similar issue before when reading from csv. Assuming it is the same:
col_name =df.columns[0]
df=df.rename(columns = {col_name:'new_name'})
The error in my case was caused by (I think) by a byte order marker in the csv or some other non-printing character being added to the first column label. df.columns returns an array of the column names. df.columns[0] gets the first one. Try printing it and seeing if something is odd with the results.
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PS On above answer by JAB - if there is clearly spaces in your column names use skipinitialspace=True in read_csv e.g.
df = pd.read_csv('/path../NavieBayes.csv',skipinitialspace=True)
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