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Say I make a pandas dataframe (I am not good at pandas, and this may not be very efficient):
import pandas as pd
colnames = ['a', 'b']
data = pd.DataFrame(columns=colnames)
df_row = ['val1', 'val2']
app = pd.Series(df_row, index=cols)
data = data.append(app, ignore_index=True)
I want to access val1 as a string, not as a pandas object.
If I do:
cell = data.iloc[[0],[0]]
type(cell)
I see that cell is of type <class 'pandas.core.frame.DataFrame'>
If I then do:
type(cell[`a'])
I see that it is <class 'pandas.core.series.Series'>
How can I get val1 as a str object and not a pandas object?
858
Select Cell Value from DataFrame Using df['col_name']. values[] We can use df['col_name']. values[] to get 1×1 DataFrame as a NumPy array, then access the first and only value of that array to get a cell value, for instance, df["Duration"].
You can extract a column of pandas DataFrame based on another value by using the DataFrame. query() method. The query() is used to query the columns of a DataFrame with a boolean expression. The blow example returns a Courses column where the Fee column value matches with 25000.
The issue for your case is that you are passing lists to iloc, you need to pass normal integers 0,0 to iloc to get the result you want -
In [85]: data.iloc[0,0]
Out[85]: 'val1'
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