熊猫Dataframe操纵

Question

Can anyone explain to me how to solve this problem.

Let's say i have a dataframe like:

Df = {'toto': ["A", "B", "C", "D"], 
      'titi': ["g", "t", "x", "z"],
      'Energy': [180, 345, 234, 654],
      'T10sec': [0.1, 0.4, 0.5, 1], 
      'T50sec': [5.3, 5.7, 8, 2]}

For this Df i've created a function like

def record(letter1, letter2, Energy_value, time):

What i want to do it's

Check if: the enter values are in this Df , if yes then

Results = Df.thecorrespondingtime[i]

Assume that for the columns 'toto' and 'titi' the input letter are in Df , two cases are possible:

Case1: the input 'Energy_value' is in Df but not the 'time' value then i have to find the range of this value and create its column and fill it with interpolation.

Case 2: the column value of 'time' exists but the input Energy value no. Here again i need to do an interpolation.

My limitations are: How to check if the 'time' column exists and how to put between two existing values. The same question for the input Energy value.

Here, what i tried:

def record(letter1, letter2, Energy_value, time='T15sec'):
    For i in range(len(Df)):
        If ((df.toto[i] == letter1) and 
            (df.titi[i] == letter2) and 
            (df.Energy[i] == Energy_value) and 
            (time in df)):

But it doesn't work. Can anyone help me?

Answer 1

If the question is basically about inserting another time column into the dataframe this would be a solution:

import pandas as np

df = pd.DataFrame({'toto': ["A", "B", "C", "D"], 
      'titi': ["g", "t", "x", "z"],
      'Energy': [180, 345, 234, 654],
      'T10sec': [0.1, 0.4, 0.5, 1], 
      'T50sec': [5.3, 5.7, 8, 2]})
df
    toto    titi    Energy  T10sec  T50sec
0   A       g       180     0.1     5.3
1   B       t       345     0.4     5.7
2   C       x       234     0.5     8.0
3   D       z       654     1.0     2.0

Add time column:

import numpy as np
time = 'T15sec'

if not time in df:
    df[time] = np.NaN

df.iloc[:, 3:] = df.iloc[:, 3:].T.sort_index().interpolate().T

df[['toto', 'titi', 'Energy', 'T10sec', time, 'T50sec']]

    toto    titi    Energy  T10sec  T15sec  T50sec
0   A       g       180     0.1     2.70    5.3
1   B       t       345     0.4     3.05    5.7
2   C       x       234     0.5     4.25    8.0
3   D       z       654     1.0     1.50    2.0