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I keep getting different attribute errors when trying to run this file in ipython...beginner with pandas so maybe I'm missing something
Code:
from pandas import Series, DataFrame import pandas as pd import json nan=float('NaN') data = [] with open('file.json') as f: for line in f: data.append(json.loads(line)) df = DataFrame(data, columns=['accepted', 'user', 'object', 'response']) clean = df.replace('NULL', nan) clean = clean.dropna() print clean.value_counts() AttributeError: 'DataFrame' object has no attribute 'value_counts' Any ideas?
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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.
value_counts is a Series method rather than a DataFrame method (and you are trying to use it on a DataFrame, clean). You need to perform this on a specific column:
clean[column_name].value_counts() It doesn't usually make sense to perform value_counts on a DataFrame, though I suppose you could apply it to every entry by flattening the underlying values array:
pd.value_counts(df.values.flatten()) To get all the counts for all the columns in a dataframe, it's just df.count()
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