In [55]:

import pandas as pd

df1 = pd.DataFrame({
    "a":[40, 70, 10],
    "b":[50, 80, 20],
    "c":[60, 90, 30]},
    index=[1, 2, 3])
print(df1)

    a   b   c
1  40  50  60
2  70  80  90
3  10  20  30

In [56]:

df2 = pd.DataFrame([
    [41, 51, 61],
    [71, 81, 91],
    [11, 21, 31]],
    index=[1, 2, 3],
    columns=['a', 'b', 'c'])
print(df2)

    a   b   c
1  41  51  61
2  71  81  91
3  11  21  31

In [57]:

df3 = pd.concat( [ df1, df2 ] )
print(df3)

    a   b   c
1  40  50  60
2  70  80  90
3  10  20  30
1  41  51  61
2  71  81  91
3  11  21  31

In [58]:

pd.concat([df1,df2], axis=1)

Out[58]:

	a	b	c	a	b	c
1	40	50	60	41	51	61
2	70	80	90	71	81	91
3	10	20	30	11	21	31

In [59]:

df3 = df3.reset_index()
print(df3)

   index   a   b   c
0      1  40  50  60
1      2  70  80  90
2      3  10  20  30
3      1  41  51  61
4      2  71  81  91
5      3  11  21  31

In [60]:

df3 = df3.drop(columns=['index'])
print(df3)

    a   b   c
0  40  50  60
1  70  80  90
2  10  20  30
3  41  51  61
4  71  81  91
5  11  21  31

In [61]:

df4 = pd.melt(df3)
print(df4)

   variable  value
0         a     40
1         a     70
2         a     10
3         a     41
4         a     71
5         a     11
6         b     50
7         b     80
8         b     20
9         b     51
10        b     81
11        b     21
12        c     60
13        c     90
14        c     30
15        c     61
16        c     91
17        c     31

In [62]:

df4.sort_values('value')

Out[62]:

	variable	value
2	a	10
5	a	11
8	b	20
11	b	21
14	c	30
17	c	31
0	a	40
3	a	41
6	b	50
9	b	51
12	c	60
15	c	61
1	a	70
4	a	71
7	b	80
10	b	81
13	c	90
16	c	91

In [63]:

df4.sort_values('value', ascending=False)

Out[63]:

	variable	value
16	c	91
13	c	90
10	b	81
7	b	80
4	a	71
1	a	70
15	c	61
12	c	60
9	b	51
6	b	50
3	a	41
0	a	40
17	c	31
14	c	30
11	b	21
8	b	20
5	a	11
2	a	10

In [64]:

df4.query('value>50')

Out[64]:

	variable	value
1	a	70
4	a	71
7	b	80
9	b	51
10	b	81
12	c	60
13	c	90
15	c	61
16	c	91

In [65]:

df4.query('value>50').query('variable=="b"')

Out[65]:

	variable	value
7	b	80
9	b	51
10	b	81

In [66]:

df4.rename(columns={'variable':'var', 'value':'val'})

Out[66]:

	var	val
0	a	40
1	a	70
2	a	10
3	a	41
4	a	71
5	a	11
6	b	50
7	b	80
8	b	20
9	b	51
10	b	81
11	b	21
12	c	60
13	c	90
14	c	30
15	c	61
16	c	91
17	c	31

In [67]:

df4['variable'].drop_duplicates()

Out[67]:

0     a
6     b
12    c
Name: variable, dtype: object

In [68]:

df4.head(5)

Out[68]:

	variable	value
0	a	40
1	a	70
2	a	10
3	a	41
4	a	71

In [69]:

df4.tail(5)

Out[69]:

	variable	value
13	c	90
14	c	30
15	c	61
16	c	91
17	c	31

In [70]:

import pandas as pd

leftDF = pd.DataFrame({'key': ['A', 'B', 'C', 'D'], 'value': [1,2,3,4]})    
rightDF = pd.DataFrame({'key': ['B', 'D', 'E', 'F'], 'value': [5,6,7,8]})

print(leftDF)
print(rightDF)

  key  value
0   A      1
1   B      2
2   C      3
3   D      4
  key  value
0   B      5
1   D      6
2   E      7
3   F      8

In [71]:

# leftDF.merge(rightDF, on='key')
# leftDF.merge(rightDF, on='key', how='inner')
pd.merge(leftDF, rightDF, on='key', how='inner')

Out[71]:

	key	value_x	value_y
0	B	2	5
1	D	4	6

In [72]:

# leftDF.merge(rightDF, on='key', how='left')
pd.merge(leftDF, rightDF, on='key', how='left')

Out[72]:

	key	value_x	value_y
0	A	1	NaN
1	B	2	5.0
2	C	3	NaN
3	D	4	6.0

In [73]:

# leftDF.merge(rightDF, on='key', how='right')
pd.merge(leftDF, rightDF, on='key', how='right')

Out[73]:

	key	value_x	value_y
0	B	2.0	5
1	D	4.0	6
2	E	NaN	7
3	F	NaN	8

In [74]:

# leftDF.merge(rightDF, on='key', how='outer')
pd.merge(leftDF, rightDF, on='key', how='outer')

Out[74]:

	key	value_x	value_y
0	A	1.0	NaN
1	B	2.0	5.0
2	C	3.0	NaN
3	D	4.0	6.0
4	E	NaN	7.0
5	F	NaN	8.0

In [74]:

	variable	value
2	a	10
5	a	11
8	b	20
11	b	21
14	c	30
17	c	31
0	a	40
3	a	41
6	b	50
9	b	51
12	c	60
15	c	61
1	a	70
4	a	71
7	b	80
10	b	81
13	c	90
16	c	91

	variable	value
16	c	91
13	c	90
10	b	81
7	b	80
4	a	71
1	a	70
15	c	61
12	c	60
9	b	51
6	b	50
3	a	41
0	a	40
17	c	31
14	c	30
11	b	21
8	b	20
5	a	11
2	a	10

	var	val
0	a	40
1	a	70
2	a	10
3	a	41
4	a	71
5	a	11
6	b	50
7	b	80
8	b	20
9	b	51
10	b	81
11	b	21
12	c	60
13	c	90
14	c	30
15	c	61
16	c	91
17	c	31

	variable	value
2	a	10
5	a	11
8	b	20
11	b	21
14	c	30
17	c	31
0	a	40
3	a	41
6	b	50
9	b	51
12	c	60
15	c	61
1	a	70
4	a	71
7	b	80
10	b	81
13	c	90
16	c	91

	variable	value
16	c	91
13	c	90
10	b	81
7	b	80
4	a	71
1	a	70
15	c	61
12	c	60
9	b	51
6	b	50
3	a	41
0	a	40
17	c	31
14	c	30
11	b	21
8	b	20
5	a	11
2	a	10

	var	val
0	a	40
1	a	70
2	a	10
3	a	41
4	a	71
5	a	11
6	b	50
7	b	80
8	b	20
9	b	51
10	b	81
11	b	21
12	c	60
13	c	90
14	c	30
15	c	61
16	c	91
17	c	31

	variable	value
2	a	10
5	a	11
8	b	20
11	b	21
14	c	30
17	c	31
0	a	40
3	a	41
6	b	50
9	b	51
12	c	60
15	c	61
1	a	70
4	a	71
7	b	80
10	b	81
13	c	90
16	c	91

	variable	value
16	c	91
13	c	90
10	b	81
7	b	80
4	a	71
1	a	70
15	c	61
12	c	60
9	b	51
6	b	50
3	a	41
0	a	40
17	c	31
14	c	30
11	b	21
8	b	20
5	a	11
2	a	10

	var	val
0	a	40
1	a	70
2	a	10
3	a	41
4	a	71
5	a	11
6	b	50
7	b	80
8	b	20
9	b	51
10	b	81
11	b	21
12	c	60
13	c	90
14	c	30
15	c	61
16	c	91
17	c	31