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 |
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