I have output that looks like this:
nutrition_info_256174499 = df1.loc[:"Salt" , "%Reference Intake*"]
print (nutrition_info_256174499)
Typical Values
Energy 5%
Fat 1%
of which saturates 1%
Carbohydrates 7%
of which sugars 2%
Fibre -
Protein 7%
Salt 6%
Name: %Reference Intake*, dtype: object
What must be done to remove both Name and dtype at end of output?
Specific rows and columns can be removed from a DataFrame object using the drop() instance method. The drop method can be specified of an axis – 0 for columns and 1 for rows. Similar to axis the parameter, index can be used for specifying rows and columns can be used for specifying columns.
The dtypes property returns data type of each column in the DataFrame.
The most straightforward way to drop a Pandas dataframe index is to use the Pandas . reset_index() method. By default, the method will only reset the index, forcing values from 0 - len(df)-1 as the index. The method will also simply insert the dataframe index into a column in the dataframe.
For printing with preserving index you can use Series.to_string()
:
df = pd.DataFrame(
{'a': [1, 2, 3], 'b': [2.23, 0.23, 2.3]},
index=['x1', 'x2', 'x3'])
s = df.loc[:'x2', 'b']
print(s.to_string())
Output:
x1 2.23
x2 0.23
.values
attribute.Example:
In [158]: s = pd.Series(['race','gender'], index=[1,2])
In [159]: print(s)
1 race
2 gender
dtype: object
In [160]: s.values
Out[160]: array(['race', 'gender'], dtype=object)
You can convert to a list or access each value:
In [161]: list(s)
Out[161]: ['race', 'gender']
print(nutrition_info_256174499.to_string())
that should remove Name: %Reference Intake*, dtype: object
in your prints
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