如何更改数据框的索引或形状

Question

我有一个形状为 2x3 的数据框，我想将其更改为 3x2，然后将其可视化。

我怎样才能两者兼顾？

这是我的代码：

avg_txn_by_mth = {
    'August': {
        'avg_cnt': txn_by_mth['August']['Count'] / 31,
        'avg_amt': txn_by_mth['August']['Amount'] / txn_by_mth['August']['Count']
    },
    'September': {
        'avg_cnt': txn_by_mth['September']['Count'] / 30, 
        'avg_amt': txn_by_mth['September']['Amount'] / txn_by_mth['September']['Count']
    },
    'October': {
        'avg_cnt': txn_by_mth['October']['Count'] / 31, 
        'avg_amt': txn_by_mth['October']['Amount'] / txn_by_mth['October']['Count']
    }
}

avg_txn_by_mth = pd.DataFrame(avg_txn_by_mth)
avg_txn_by_mth

Answer 1

使用pandas.DataFrame.transpose

import pandas as pd
import matplotlib.pyplot as plt

data = {'August': {'avg_amt': 2.0, 'avg_cnt': 9.67741935483871},
        'October': {'avg_amt': 1.6, 'avg_cnt': 16.129032258064516},
        'September': {'avg_amt': 1.75, 'avg_cnt': 13.333333333333334}}

df = pd.DataFrame(data)

# display
           August    October  September
avg_amt  2.000000   1.600000   1.750000
avg_cnt  9.677419  16.129032  13.333333

# transpose
dft = df.T

# display
           avg_amt    avg_cnt
August        2.00   9.677419
October       1.60  16.129032
September     1.75  13.333333

# plot
p = dft.plot()

如何更改数据框的索引或形状

How to change the index or shape of a dataframe

visualization

dataframe

python-3.x

pandas