CODEWITHSUNDEEP
pythonpandasnumpy
Yadhu
Yadhu

Reputation: 125

adding new rows to an existing dataframe

enter image description here

This is my dataframe. How to I add max_value, min_value, mean_value, median_value names to rows so that my index values will be like

0

1

2

3

4

max_value

min_value

mean_value

median_value

Could anyone help me in solving this

Upvotes: 1

Views: 72

Answers (3)

Yadhu
Yadhu

Reputation: 125

This worked well and fine:

df1 = df.copy()
df.loc['max']=df1.max()
df.loc['min']=df1.min()
df.loc['mean']=df1.mean()
df.loc['median']=df1.median()

Upvotes: 1

Mohamed Thasin ah
Mohamed Thasin ah

Reputation: 11192

one Way is,

Thanks to @jezrael for the help.

df = pd.DataFrame(np.random.randint(0,100,size=(5, 4)), columns=list('ABCD'))
df1=df.copy()

#column wise calc
df.loc['max']=df1.max()
df.loc['min']=df1.min()
df.loc['mean']=df1.mean()
df.loc['median']=df1.median()

#row wise calc
df['max']=df1.max(axis=1)
df['min']=df1.min(axis=1)
df['mean']=df1.mean(axis=1)
df['median']=df1.median(axis=1)

O/P:

           A     B     C     D   max   min   mean  median
0       49.0  91.0  16.0  17.0  91.0  16.0  43.25    33.0
1       20.0  42.0  86.0  60.0  86.0  20.0  52.00    51.0
2       32.0  25.0  94.0  13.0  94.0  13.0  41.00    28.5
3       40.0   1.0  66.0  31.0  66.0   1.0  34.50    35.5
4       18.0  30.0  67.0  31.0  67.0  18.0  36.50    30.5
max     49.0  91.0  94.0  60.0   NaN   NaN    NaN     NaN
min     18.0   1.0  16.0  13.0   NaN   NaN    NaN     NaN
mean    31.8  37.8  65.8  30.4   NaN   NaN    NaN     NaN
median  32.0  30.0  67.0  31.0   NaN   NaN    NaN     NaN

Upvotes: 2

jezrael
jezrael

Reputation: 862671

If want add rows use add DataFrame.agg:

df1 = df.append(df.agg(['max','min','mean','median']))

If want add columns use assign with min, max, mean and median:

df2 = df.assign(max_value=df.max(axis=1),
                min_value=df.min(axis=1),
                mean_value=df.mean(axis=1),
                median_value=df.median(axis=1))

Upvotes: 3

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