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Pandas DataFrame column difference of max and min value


Pandas DataFrame column difference of max and min value

By : Audumber Jagdale
Date : November 18 2020, 07:00 PM
hope this fix your issue I want to get the difference of max and min vale of a column. , Use .ptp() (peak-to-peak) to get the max-minus-min:
code :
In [1]: import pandas as pd                                                     

In [2]: import numpy as np                                                      

In [3]: np.random.seed(444)                                                     

In [4]: df = pd.DataFrame({"Glucose": np.random.randint(0, 10000, size=100)}) 

In [5]: df['Glucose'].ptp()                                                                                                                                   
Out[5]: 9947


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min vs max difference in pandas dataframe by column

min vs max difference in pandas dataframe by column


By : Emeraldo
Date : March 29 2020, 07:55 AM
like below fixes the issue I have a dataframe like below, , For dictionary use dict comprehension:
code :
d = {k:[v] for k, v in df.max().sub(df.min()).items()}
print (d)
{'50': [2.1799999999999997], '40': [2.2600000000000002], '60': [1.9999999999999996]}
a = df.max().sub(df.min()).idxmin()
print (a)
60
print (df.max().sub(df.min()))
40    2.26
50    2.18
60    2.00
dtype: float64
pandas - how do i get the difference from a dataframe on the same column

pandas - how do i get the difference from a dataframe on the same column


By : astha avasthy
Date : March 29 2020, 07:55 AM
To fix the issue you can do I have 2 identical dataframes apart from the 'value' column, need to get the difference of the 2 dataframes on the 'value' column based on year+name+month columns, and append that to the data set. , Check with groupby and diff after sort_values
code :
y2=y1.copy()
y2=y2.sort_values('year')
y2['value']=y2.groupby(['name','month']).value.diff()
y1=y1.append(y2.dropna().assign(year='diff'))
y1
    year name   month  value
0   2018  abc  Jan-18  100.0
1   2018  xyz  Feb-18  200.0
2   2018  pqr  Mar-18  300.0
3   2018  stu  Apr-18  400.0
4   2018  hij  May-18  500.0
5   2018  efg  Jun-18  600.0
6   2019  abc  Jan-18  700.0
7   2019  xyz  Feb-18  300.0
8   2019  pqr  Mar-18  200.0
9   2019  stu  Apr-18  500.0
10  2019  hij  May-18  600.0
11  2019  efg  Jun-18  100.0
6   diff  abc  Jan-18  600.0
7   diff  xyz  Feb-18  100.0
8   diff  pqr  Mar-18 -100.0
9   diff  stu  Apr-18  100.0
10  diff  hij  May-18  100.0
11  diff  efg  Jun-18 -500.0
Add column with difference between dates pandas DataFrame

Add column with difference between dates pandas DataFrame


By : Mir muhammad Qureshi
Date : March 29 2020, 07:55 AM
I wish this helpful for you It's easily solved using to use groupby.
code :
ddf = df.groupby('season').apply(lambda x : x['Date'] - x.loc[x['Holiday_Name'] == 'Easter']['Date'].iloc[0]).reset_index()
df['difference'] = ddf['Date']

  season       Date Holiday_Name difference
0  12-13 2012-11-01          NaN  -150 days
1  12-13 2012-11-02          Nan  -149 days
2  12-13 2013-03-31       Easter     0 days
3  12-13 2013-04-05          NaN     5 days
4  13-14 2013-11-01          NaN  -170 days
5  13-14 2014-04-18          Nan    -2 days
6  13-14 2014-04-20       Easter     0 days
7  13-14 2014-04-22          Nan     2 days
Find out the difference in two dataframe with same column pandas

Find out the difference in two dataframe with same column pandas


By : JoaBo
Date : March 29 2020, 07:55 AM
This might help you I have three dataframe as shown below , For each day is necessary copy DataFrame to new one:
code :
df1 = df.copy()
df_added = df[~df['Unit_ID'].isin(df1['Unit_ID'])]
print (df2)
   Unit_ID  Price
0        1     10
1        2     20
2        3     10
3        4     15
4        5     20

print (df3)
   Unit_ID  Price
0        1     10
1        2     20
2        3     10
3        4     15
4        5     20
5        6     80

df_added = df3[~df3['Unit_ID'].isin(df2['Unit_ID'])]
print (df_added)
   Unit_ID  Price
5        6     80
Pandas - Iterate through dataframe and calculate difference between column value and previous column.

Pandas - Iterate through dataframe and calculate difference between column value and previous column.


By : Robbie Bouchoms
Date : March 29 2020, 07:55 AM
hope this fix your issue I have a dataframe called "df" that consists of Date, ID, and Activity that is sorted both on "date" and "id" in order to group IDs together then arrange them chronologically earliest to latest. , Use groupby with diff
code :
df.assign(Duration=df.groupby('ID').Date.diff().fillna(0))

                 Date    ID  Activity Duration
0 2018-04-12 07:58:00  1111         1 00:00:00
1 2018-04-12 08:40:00  1111         0 00:42:00
2 2018-04-12 08:42:00  1111         1 00:02:00
3 2018-04-12 09:26:00  1111         0 00:44:00
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