pre-view/CS50-raw · Datasets at Hugging Face

text stringlengths 1 81	start float64 0 10.1k	duration float64 0 24.9
I should see in this case that insert didn't work.	1,011.4	6.01
So these constraints are really guardrails against me,	1,017.41	3.11
against other users to adding values that we really	1,020.52	2.46
shouldn't add to our table.	1,022.98	3.5
OK, so presumably here, we're onto something by adding some rows.	1,026.48	5.92
But if the museum acquires more than one item, maybe 100 at a time,	1,032.4	5.33
I don't want to be the programmer who's sitting there writing 100 INSERT INTO.	1,037.73	3.389
That's like not what I want to do.	1,041.119	1.621
There's probably a better way to do this.	1,042.74	1.89
[? And ?] [? we ?] show you one way to do this.	1,044.63	2.41
One way is to instead of inserting one row, like this, to instead insert	1,047.04	5.15
multiple separated by commas.	1,052.19	2.71
So here, I might say this is my first row for each of these columns.	1,054.9	4.97
This is my second row, again, for each of these columns,	1,059.87	3.21
and so on and so forth.	1,063.08	2.29
And it's worth noting, this is not just a manner of convenience.	1,065.37	4.16
Like if I tried to insert 100 rows, this is certainly convenient for me.	1,069.53	4.6
But it's also most often in most cases going	1,074.13	3.08
to be faster for me to insert 100 rows in one go,	1,077.21	3.99
than to insert one row 100 times.	1,081.2	3.19
So this is both a convenience thing for programmers	1,084.39	2.54
and also an efficiency thing to actually optimize your database as well.	1,086.93	4.81
So let's try this syntax now to avoid me sitting there for hours and hours	1,091.74	4.61
writing many insert interviews.	1,096.35	1.89
I'll go back to my computer.	1,098.24	2.22
And this time, let's say we got two paintings at once.	1,100.46	3.48
We got two.	1,103.94	0.81
So I'll try to add both of them.	1,104.75	1.92
I'll say INSERT INTO the "collections" table.	1,106.67	3.84
And again, I want to keep adding to my "title" column, my "accession_number"	1,110.51	5.22
column, and even my "acquired" column, like this.	1,115.73	4.47
Now, I want to add in some values.	1,120.2	2.44
So I'll type VALUES here.	1,122.64	1.73
And as a matter of style, let me just say I'll make a new line.	1,124.37	4.02
I'll Enter here.	1,128.39	1.26
And now I can type each of my new rows on their very own line.	1,129.65	4.71
So again, I'll type all of the values that I want in my first row.	1,134.36	4.86
I might call this one "Imaginative landscape."	1,139.22	3
We got this one back in--	1,142.22	1.565
actually, we don't quite know when we got this one.	1,143.785	2.125
If I type 56.496 is the accession number, like, yeah, 56.496.	1,145.91	6.3
The MFA actually doesn't know when they got this painting.	1,152.21	3.22
So if they don't know, let's just insert NULL.	1,155.43	3.38
This is intentionally left blank.	1,158.81	3.99
This is my first row.	1,162.8	1.35
Now, I want to add a second one in one go.	1,164.15	2.82
I'll follow this up with a comma.	1,166.97	1.72
And now, I'll type out my next set of values.	1,168.69	3.56
This next one we acquired is called "Peonies and butterfly."	1,172.25	3.75
Now, I'll say the [? accession ?] [? number ?] is 06.1899.	1,176	4.71
And we got this one-- it was back in 1906-01-01 now I'll hit semicolon here.	1,180.71	7.86
And now, if I hit Enter, nothing happens.	1,188.57	3.73
But if I type Select [? star ?] FROM "collections" semicolon,	1,192.3	5.03
what do we see, but now two new rows being inserted.	1,197.33	4.63
So a handy way to insert more than one value.	1,201.96	3.54
And also, if you have a lot of values, a more efficient way as well.	1,205.5	5.01
So we pause here.	1,210.51	1.52
And ask what questions we have on INSERT INTO, Whether adding one row	1,212.03	5.9
or adding multiple.	1,217.93	1.62
Let's go to [INAUDIBLE].	1,219.55	1.77
SPEAKER 4: [? So ?] [? imagine ?] you are [? writing ?] [? code ?]	1,221.32	2.75
or inserting a row, so by mistake you have entered the wrong spelling	1,224.07	4.63
of the title, so how we will rename it?	1,228.7	3.017
SPEAKER 1: A great question too.	1,231.717	1.333
And often as is the case with me, I make typos all the time.	1,233.05	2.85
I might add the artwork title and misspell it for instance.	1,235.9	4.14
Well, in that case, I can't use INSERT INTO to correct it,	1,240.04	4.56
but I can use a new statement we'll see a little later called [? update. ?]	1,244.6	3.81
And so with [? update, ?] you can actually	1,248.41	1.8
change the spellings of things.	1,250.21	1.62
And we'll see that a little later today.	1,251.83	2.1
But great question to peek ahead as well.	1,253.93	3.84
OK, so let's keep going here.	1,257.77	2.5
Let's think about how we can keep adding values to our data set.	1,260.27	4.23
And so far we've seen INSERT INTO with one row and with multiple.	1,264.5	5.12
But one more way to keep in mind is you might already	1,269.62	4.02
have your data, perhaps in some other format.	1,273.64	3.66
And one common format looks a bit like this on our screen over here.	1,277.3	5.64
This file is called CSV for Comma Separated Values.	1,282.94	6.81
Now, why Comma Separated Values?	1,289.75	2.01
Well, let's just look at it.	1,291.76	1.59
Here we see some presumably column or column names,	1,293.35	3.36
like [? id, ?] [? title, ?] [? accession number, ?]	1,296.71	2.82
and [? acquired, ?] but what separates these column names?	1,299.53	3.45
Well, it looks like commas--	1,302.98	1.53
"id" comma "title," comma "accession_number," and so on.	1,304.51	3.96
Every row is still its own row.	1,308.47	2.88
That makes sense here.	1,311.35	1.32
But now, those row values are also separated by commas.	1,312.67	4.74
Notice here, the first value before the first comma	1,317.41	3.69
corresponds to the first column, this id is 1.	1,321.1	4.11
Similarly, the next Comma Separated Value Profusion of flowers	1,325.21	3.84
belongs to that next column here-- "title" as well,	1,329.05	3.4
and so on and so forth.	1,332.45	1.62
You could if you wanted to draw a snaky line	1,334.07	2.75
to see how these columns correspond down our file here.	1,336.82	4.96
Now, you might often have data already in this format.	1,341.78	3.94
And it's actually pretty convenient to try	1,345.72	1.75
to import this data into SQLite into your very own table	1,347.47	4.29
so you can use [? SQL ?] on it.	1,351.76	2.41

I should see in this case that insert didn't work.

1,011.4

6.01

So these constraints are really guardrails against me,

1,017.41

3.11

against other users to adding values that we really

1,020.52

2.46

shouldn't add to our table.

1,022.98

3.5

OK, so presumably here, we're onto something by adding some rows.

1,026.48

5.92

But if the museum acquires more than one item, maybe 100 at a time,

1,032.4

5.33

I don't want to be the programmer who's sitting there writing 100 INSERT INTO.

1,037.73

3.389

That's like not what I want to do.

1,041.119

1.621

There's probably a better way to do this.

1,042.74

1.89

[? And ?] [? we ?] show you one way to do this.

1,044.63

2.41

One way is to instead of inserting one row, like this, to instead insert

1,047.04

5.15

multiple separated by commas.

1,052.19

2.71

So here, I might say this is my first row for each of these columns.

1,054.9

4.97

This is my second row, again, for each of these columns,

1,059.87

3.21

and so on and so forth.

1,063.08

2.29

And it's worth noting, this is not just a manner of convenience.

1,065.37

4.16

Like if I tried to insert 100 rows, this is certainly convenient for me.

1,069.53

4.6

But it's also most often in most cases going

1,074.13

3.08

to be faster for me to insert 100 rows in one go,

1,077.21

3.99

than to insert one row 100 times.

1,081.2

3.19

So this is both a convenience thing for programmers

1,084.39

2.54

and also an efficiency thing to actually optimize your database as well.

1,086.93

4.81

So let's try this syntax now to avoid me sitting there for hours and hours

1,091.74

4.61

writing many insert interviews.

1,096.35

1.89

I'll go back to my computer.

1,098.24

2.22

And this time, let's say we got two paintings at once.

1,100.46

3.48

We got two.

1,103.94

0.81

So I'll try to add both of them.

1,104.75

1.92

I'll say INSERT INTO the "collections" table.

1,106.67

3.84

And again, I want to keep adding to my "title" column, my "accession_number"

1,110.51

5.22

column, and even my "acquired" column, like this.

1,115.73

4.47

Now, I want to add in some values.

1,120.2

2.44

So I'll type VALUES here.

1,122.64

1.73

And as a matter of style, let me just say I'll make a new line.

1,124.37

4.02

I'll Enter here.

1,128.39

1.26

And now I can type each of my new rows on their very own line.

1,129.65

4.71

So again, I'll type all of the values that I want in my first row.

1,134.36

4.86

I might call this one "Imaginative landscape."

1,139.22

3

We got this one back in--

1,142.22

1.565

actually, we don't quite know when we got this one.

1,143.785

2.125

If I type 56.496 is the accession number, like, yeah, 56.496.

1,145.91

6.3

The MFA actually doesn't know when they got this painting.

1,152.21

3.22

So if they don't know, let's just insert NULL.

1,155.43

3.38

This is intentionally left blank.

1,158.81

3.99

This is my first row.

1,162.8

1.35

Now, I want to add a second one in one go.

1,164.15

2.82

I'll follow this up with a comma.

1,166.97

1.72

And now, I'll type out my next set of values.

1,168.69

3.56

This next one we acquired is called "Peonies and butterfly."

1,172.25

3.75

Now, I'll say the [? accession ?] [? number ?] is 06.1899.

1,176

4.71

And we got this one-- it was back in 1906-01-01 now I'll hit semicolon here.

1,180.71

7.86

And now, if I hit Enter, nothing happens.

1,188.57

3.73

But if I type Select [? star ?] FROM "collections" semicolon,

1,192.3

5.03

what do we see, but now two new rows being inserted.

1,197.33

4.63

So a handy way to insert more than one value.

1,201.96

3.54

And also, if you have a lot of values, a more efficient way as well.

1,205.5

5.01

So we pause here.

1,210.51

1.52

And ask what questions we have on INSERT INTO, Whether adding one row

1,212.03

5.9

or adding multiple.

1,217.93

1.62

Let's go to [INAUDIBLE].

1,219.55

1.77

SPEAKER 4: [? So ?] [? imagine ?] you are [? writing ?] [? code ?]

1,221.32

2.75

or inserting a row, so by mistake you have entered the wrong spelling

1,224.07

4.63

of the title, so how we will rename it?

1,228.7

3.017

SPEAKER 1: A great question too.

1,231.717

1.333

And often as is the case with me, I make typos all the time.

1,233.05

2.85

I might add the artwork title and misspell it for instance.

1,235.9

4.14

Well, in that case, I can't use INSERT INTO to correct it,

1,240.04

4.56

but I can use a new statement we'll see a little later called [? update. ?]

1,244.6

3.81

And so with [? update, ?] you can actually

1,248.41

1.8

change the spellings of things.

1,250.21

1.62

And we'll see that a little later today.

1,251.83

2.1

But great question to peek ahead as well.

1,253.93

3.84

OK, so let's keep going here.

1,257.77

2.5

Let's think about how we can keep adding values to our data set.

1,260.27

4.23

And so far we've seen INSERT INTO with one row and with multiple.

1,264.5

5.12

But one more way to keep in mind is you might already

1,269.62

4.02

have your data, perhaps in some other format.

1,273.64

3.66

And one common format looks a bit like this on our screen over here.

1,277.3

5.64

This file is called CSV for Comma Separated Values.

1,282.94

6.81

Now, why Comma Separated Values?

1,289.75

2.01

Well, let's just look at it.

1,291.76

1.59

Here we see some presumably column or column names,

1,293.35

3.36

like [? id, ?] [? title, ?] [? accession number, ?]

1,296.71

2.82

and [? acquired, ?] but what separates these column names?

1,299.53

3.45

Well, it looks like commas--

1,302.98

1.53

"id" comma "title," comma "accession_number," and so on.

1,304.51

3.96

Every row is still its own row.

1,308.47

2.88

That makes sense here.

1,311.35

1.32

But now, those row values are also separated by commas.

1,312.67

4.74

Notice here, the first value before the first comma

1,317.41

3.69

corresponds to the first column, this id is 1.

1,321.1

4.11

Similarly, the next Comma Separated Value Profusion of flowers

1,325.21

3.84

belongs to that next column here-- "title" as well,

1,329.05

3.4

and so on and so forth.

1,332.45

1.62

You could if you wanted to draw a snaky line

1,334.07

2.75

to see how these columns correspond down our file here.

1,336.82

4.96

Now, you might often have data already in this format.

1,341.78

3.94

And it's actually pretty convenient to try

1,345.72

1.75

to import this data into SQLite into your very own table

1,347.47

4.29

so you can use [? SQL ?] on it.

1,351.76

2.41