I would like to use unique in Pandas, but I don't know what to do because I can only take it out in Dataframe.

The data (df)

being read by Pandas

ab
    -0.2    -0.200
    -0.2    -0.195
    -0.2    -0.190
    -0.2    -0.185
    -0.2    -0.180

I want to retrieve the data regardless of the column name, so I'm retrieving it using df.iloc[:,[0]].I would like to use unique for this extracted data.
However, in the case of df.iloc[:,[0]], I would like df.iloc[:,[0]].unique, but AttributeError: 'DataFrame' object has no attribute 'unique' does not work.What should I do?

python pandas

2022-12-04 23:56

3 Answers

There are several ways to remove the pandas.Series from the column

df['a']
df.a
df[df.columns[0]]
df.iloc[:,0])

df.iloc[:,[0]] lists, so the result is DataFrame

df[df.columns[0]].unique()

# array([-0.2])

2022-12-05 01:14

Your question may be a little confusing, but I'll answer how to get a unique array of elements from the data frame.

import pandas as pd
import numpy as np

df = pd.DataFrame([-0.2, -0.200], [-0.2, -0.195],
                   [-0.2, -0.190], [-0.2, -0.185],
                   [-0.2, -0.180]], columns=['a', 'b'])

u1=np.unique(df.iloc[:,[0]].values)#original example
u2 = np.unique(df.values)# all elements

print(u1); print(u2)

 [-0.2]
[-0.2   -0.195 -0.19  -0.185 -0.18 ]

2022-12-05 01:42

df.iloc[:,0].unique()), but if you are concerned with the pandas.DataFrame type, you can use the pd.DataFrame.apply() method.However, in this case, the output is also of type pandas.DataFrame.

print(df.iloc[:,[0]].apply(pd.Series.unique))
print(df.iloc[:, [1]].apply(pd.Series.unique))

#      a
# 0 -0.2
#
#        b
# 0 -0.200
# 1 -0.195
# 2 -0.190
# 3 -0.185
# 4 -0.180

2022-12-05 06:09

If you have any answers or tips

Popular Tags

python x 4647

android x 1593

java x 1494

javascript x 1427

c x 927

c++ x 878

ruby-on-rails x 696

php x 692

python3 x 685

html x 656