如何将循环中的值存储到数据帧中？

Question

我已经创建了一个循环来生成一些值。我想把这些值存储在一个数据框中。例如，完成一个循环，追加到第一行。

def calculate (allFiles):

    result = pd.DataFrame(columns = ['Date','Mid Ebb Total','Mid Flood Total','Mid Ebb Control','Mid Flood Control'])

    total_Mid_Ebb = 0
    total_Mid_Flood = 0
    total_Mid_EbbControl = 0
    total_Mid_FloodControl = 0

    for file_ in allFiles:
        xls = pd.ExcelFile(file_)
        df = xls.parse('General Impact')
        Mid_Ebb = df[df['Tidal Mode'] == "Mid-Ebb"] #filter 
        Mid_Ebb_control = df[df['Station'].isin(['C1','C2','C3'])] #filter control
        Mid_Flood = df[df['Tidal Mode'] == "Mid-Flood"] #filter
        Mid_Flood_control = df[df['Station'].isin(['C1','C2','C3', 'SR2'])] #filter control
        total_Mid_Ebb += Mid_Ebb.Station.nunique() #count unique stations = sample number
        total_Mid_Flood += Mid_Flood.Station.nunique()
        total_Mid_EbbControl += Mid_Ebb_control.Station.nunique()
        total_Mid_FloodControl += Mid_Flood_control.Station.nunique()

    Mid_Ebb_withoutControl = total_Mid_Ebb - total_Mid_EbbControl
    Mid_Flood_withoutControl = total_Mid_Flood - total_Mid_FloodControl

    print('Ebb Tide: The total number of sample is {}. Number of sample without control station is {}. Number of sample in control station is {}'.format(total_Mid_Ebb, Mid_Ebb_withoutControl, total_Mid_EbbControl))
    print('Flood Tide: The total number of sample is {}. Number of sample without control station is {}. Number of sample in control station is {}'.format(total_Mid_Flood, Mid_Flood_withoutControl, total_Mid_FloodControl))

dataframe结果包含4列。日期是固定的。我想把total_Mid_eb，Mid_eb_without control，total_Mid_ebc控制到数据帧。

Answer 1

下面是在循环的每次迭代之后加载数据帧中每列数据的示例。虽然这不是唯一的方法，但它有助于更好地理解概念。

必要的进口

import pandas as pd
from random import randint

首先定义一个由5列组成的空数据框以匹配您的问题

df = pd.DataFrame(columns=['A','B','C','D','E'])

接下来，我们遍历for循环并使用randint()生成值，然后一次向每个列添加一个值，每个列一直以“a”开头，一直到“E”

for i in range(5): #add 5 rows of data
    df.loc[i, ['A']] = randint(0,99)
    df.loc[i, ['B']] = randint(0,99)
    df.loc[i, ['C']] = randint(0,99)
    df.loc[i, ['D']] = randint(0,99)
    df.loc[i, ['E']] = randint(0,99)

我们得到一个有5行填充的DF。

>>> df
    A   B   C   D   E
0   4  74  71  37  90
1  41  80  77  81   8
2  14  16  82  98  89
3   1  77   3  56  91
4  34   9  85  44  19

希望以上的帮助和您能够为您的需要量身打造。