How to use Pandas 2

1 This article

Make a note of various operation methods for DataFrame type data.

2 Contents

2-1 Multi-Index type DataFrame data Display data of only a specific index.

sample.py


import pandas as pd
import numpy as np
idx = pd.IndexSlice

#Define data.
dat = [
    [100,'2019-07-01','9997','740'],
    [100,'2019-07-02','9997','749'],
    [100,'2019-07-03','9997','757'],
    [200,'2019-07-01','9997','769'],
    [200,'2019-07-02','9997','762'],
    [200,'2019-07-03','9997','760']
]

#Store dat in DataFrame type variable df.
df = pd.DataFrame(dat,columns=["A","B","C","D"])

#A,Specify column B as index.
df=df.set_index(["A","B"])

print("Show df","\n",df)

#index=Extract 100 data.
df=df.loc[idx[100, :], :]

print("df to index=Extract 100 data.","\n",df)


#index=100,Extract the data in column D.
df=df.loc[idx[100, :], ["D"]]

print("df to index=100,Extract the data in column D.","\n",df)


Execution result

Show df
                    C    D
A   B                    
100 2019-07-01  9997  740
    2019-07-02  9997  749
    2019-07-03  9997  757
200 2019-07-01  9997  769
    2019-07-02  9997  762
    2019-07-03  9997  760
df to index=Extract 100 data.
                    C    D
A   B                    
100 2019-07-01  9997  740
    2019-07-02  9997  749
    2019-07-03  9997  757


df to index=100,Extract the data in column D.
                   D
A   B              
100 2019-07-01  740
    2019-07-02  749
    2019-07-03  757

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